Dynamic redistribution of parity groups

ABSTRACT

A system and method for dynamic redistribution of parity groups is described. The system and method for dynamic redistribution of parity groups operates on a computer storage system that includes a plurality of disk drives for storing parity groups. Each parity group includes storage blocks. The storage blocks include one or more data blocks and a parity block that is associated with the data blocks. Each of the storage blocks is stored on a separate disk drive such that no two storage blocks from a given parity set reside on the same disk drive. The computer system further includes a redistribution module to dynamically redistribute parity groups by combining some parity groups to improve storage efficiency.

REFERENCE TO RELATED APPLICATIONS

The present application claims priority benefit under 35 U.S.C. § 119(e)from all of the following U.S. Provisional Applications, the contents ofwhich are hereby incorporated by reference in their entirety:

-   -   U.S. Provisional Application No. 60/264671, filed Jan. 29, 2001,        titled “DYNAMICALLY DISTRIBUTED FILE SYSTEM”;    -   U.S. Provisional Application No. 60/264694, filed Jan. 29, 2001,        titled “A DATA PATH ACCELERATOR ASIC FOR HIGH PERFORMANCE        STORAGE SYSTEMS”;    -   U.S. Provisional Application No. 60/264672, filed Jan. 29, 2001,        titled “INTEGRATED FILE SYSTEM/PARITY DATA PROTECTION”;    -   U.S. Provisional Application No. 60/264673, filed Jan. 29, 2001,        titled “DISTRIBUTED PARITY DATA PROTECTION”;    -   U.S. Provisional Application No. 60/264670, filed Jan. 29, 2001,        titled “AUTOMATIC IDENTIFICATION AND UTILIZATION OF RESOURCES IN        A DISTRIBUTED FILE SERVER”;    -   U.S. Provisional Application No. 60/264669, filed Jan. 29, 2001,        titled “DATA FLOW CONTROLLER ARCHITECTURE FOR HIGH PERFORMANCE        STORAGE SYSTEMS”;    -   U.S. Provisional Application No. 60/264668, filed Jan. 29, 2001,        titled “ADAPTIVE LOAD BALANCING FOR A DISTRIBUTED FILE SERVER”;        and    -   U.S. Provisional Application No. 60/302424, filed Jun. 29, 2001,        titled “DYNAMICALLY DISTRIBUTED FILE SYSTEM”.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention relates to the field of data storage and management. Moreparticularly, this invention relates to high-performance mass storagesystems and methods for data storage, backup, and recovery.

2. Description of the Related Art

In modem computer systems, collections of data are usually organized andstored as files. A file system allows users to organize, access, andmanipulate these files and also performs administrative tasks such ascommunicating with physical storage components and recovering fromfailure. The demand for file systems that provide high-speed, reliable,concurrent access to vast amounts of data for large numbers of users hasbeen steadily increasing in recent years. Often such systems use aRedundant Array of Independent Disks (RAID) technology, whichdistributes the data across multiple disk drives, but provides aninterface that appears to users as one, unified disk drive system,identified by a single drive letter. In a RAID system that includes morethan one array of disks, each array is often identified by a uniquedrive letter, and in order to access a given file, a user must correctlyidentify the drive letter for the disk array on which the file resides.Any transfer of files from one disk array to another and any addition ofnew disk arrays to the system must be made known to users so that theycan continue to correctly access the files.

RAID systems effectively speed up access to data over single-disksystems, and they allow for the regeneration of data lost due to a diskfailure. However, they do so by rigidly prescribing the configuration ofsystem hardware and the block size and location of data stored on thedisks. Demands for increases in storage capacity that are transparent tothe users or for hardware upgrades that lack conformity with existingsystem hardware cannot be accommodated, especially while the system isin use. In addition, such systems commonly suffer from the problem ofdata fragmentation, and they lack the flexibility necessary tointelligently optimize use of their storage resources.

RAID systems are designed to provide high-capacity data storage withbuilt-in reliability mechanisms able to automatically reconstruct andrestore saved data in the event of a hardware failure or datacorruption. In conventional RAID technology, techniques includingspanning, mirroring, and duplexing are used to create a data storagedevice from a plurality of smaller single disk drives with improvedreliability and storage capacity over conventional disk systems. RAIDsystems generally incorporate a degree of redundancy into the storagemechanism to permit saved data to be reconstructed in the event ofsingle (or sometimes double) disk failure within the disk array. Saveddata is further stored in a predefined manner that is dependent on afixed algorithm to distribute the information across the drives of thearray. The manner of data distribution and data redundancy within thedisk array impacts the performance and usability of the storage systemand may result in substantial tradeoffs between performance,reliability, and flexibility.

A number of RAID configurations have been proposed to map data acrossthe disks of the disk array. Some of the more commonly recognizedconfigurations include RAID-1, RAID-2, RAID-3, RAID-4, and RAID-5.

In most RAID systems, data is sequentially stored in data stripes and aparity block is created for each data stripe. The parity block containsinformation derived from the sequence and composition of the data storedin the associated data stripe. RAID arrays can reconstruct informationstored in a particular data stripe using the parity information,however, this configuration imposes the requirement that records spanacross all drives in the array resulting in a small stripe size relativeto the stored record size.

FIG. 21 illustrates the data mapping approach used in many conventionalRAID storage device implementations. Although the diagram correspondsmost closely to RAID-3 or RAID-4 mapping schemas, other RAIDconfigurations are organized in a similar manner. As previouslyindicated, each RAID configuration uses a striped disk array 2110 thatlogically combines two or more disk drives 2115 into a single storageunit. The storage space of each drive 2115 is organized by partitioningthe space on the drives into stripes 2120 that are interleaved so thatthe available storage space is distributed evenly across each drive.

Information or files are stored on the disk array 2110. Typically, thewriting of data to the disks occurs in a parallel manner to improveperformance. A parity block is constructed by performing a logicaloperation (exclusive OR) on the corresponding blocks of the data stripeto create a new block of data representative of the result of thelogical operation. The result is termed a parity block and is written toa separate area 2130 within the disk array. In the event of datacorruption within a particular disk of the array 10, the parityinformation is used to reconstruct the data using the information storedin the parity block in conjunction with the remaining non-corrupted datablocks.

In the RAID architecture, multiple disks a typically mapped to a single‘virtual disk’. Consecutive blocks of the virtual disk are mapped by astrictly defined algorithm to a set of physical disks with no file levelawareness. When the RAID system is used to host a conventional filesystem, it is the file system that maps files to the virtual disk blockswhere they may be mapped in a sequential or non-sequential order in aRAID stripe. The RAID stripe may contain data from a single file or datafrom multiple files if the files are small or the file system is highlyfragmented.

The aforementioned RAID architecture suffers from a number of drawbacksthat limit its flexibility and scalability for use in reliable storagesystems. One problem with existing RAID systems is that the datastriping is designed to be used in conjunction with disks of the samesize. Each stripe occupies a fixed amount of disk space and the totalnumber of stripes allowed in the RAID system is limited by the capacityof the smallest disk in the array. Any additional space that may bepresent on drives having a capacity larger than the smallest drive goesunused as the RAID system lacks the ability to use the additional space.This further presents a problem in upgrading the storage capacity of theRAID system, as all of the drives in the array must be replaced withlarger capacity drives if additional storage space is desired.Therefore, existing RAID systems are inflexible in -terms of their drivecomposition, increasing the cost and inconvenience to maintain andupgrade the storage system.

A further problem with conventional RAID arrays resides in the rigidorganization of data on the disks of the RAID array. As previouslydescribed, this organization typically does not use available disk spacein an efficient manner. These systems further utilize a single fixedblock size to store data which is implemented with the restriction ofsequential file storage along each disk stripe. Data storage in thismanner is typically inefficient as regions or gaps of disk space may gounused due to the file organization restrictions. Furthermore, the fixedblock size of the RAID array is not able to distinguish between largefiles, which benefit from larger block size, and smaller files, whichbenefit from smaller block size for more efficient storage and reducedwasted space.

Although conventional RAID configurations are characterized as beingfault-tolerant, this capability is typically limited to single diskfailures. Should more than one (or two) disk fail or become inoperablewithin the RAID array before it can be replaced or repaired there is thepotential for data loss. This problem again arises from the rigidstructure of data storage within the array that utilizes sequential datastriping. This problem is further exacerbated by the lack of ability ofthe RAID system to flexibly redistribute data to other disk areas tocompensate for drive faults. Thus, when one drive becomes inoperablewithin the array, the likelihood of data loss increases significantlyuntil the drive is replaced resulting in increased maintenance andmonitoring requirements when using conventional RAID systems.

With respect to conventional data storage systems or other computernetworks, conventional load balancing includes a variety of drawbacks.For example, decisions relating to load balancing are typicallycentralized in one governing process, one or more system administrators,or combinations thereof. Accordingly, such systems have a single pointof failure, such as the governing process or the system administrator.Moreover, load balancing occurs only when the centralized process orsystem administrator can organize performance data, make a decision, andthen transmit that decision throughout the data storage system orcomputer network. This often means that the such load balancing can beslow to react, difficult to optimize for a particular server, anddifficult to scale as the available resources expand or contract. Inaddition, conventional load balancing typically is limited to balancingprocessing and communications activity between servers only.

SUMMARY OF THE INVENTION

The present invention solves these and other problems by providing adynamically distributed file system that accommodates current demandsfor high capacity, throughput, and reliability, while presenting to theusers a single-file-system interface that appears to include every filein the system on a single server or drive. In this way, the file systemis free to flexibly, transparently, and on-the-fly distribute andaugment physical storage of the files in any manner that suits itsneeds, across disk drives, and across servers, and users can freelyaccess any file without having specific knowledge of the files currentphysical location.

One embodiment includes a storage device and architecture whichpossesses features such as transparent scalability where disks ofnon-identical capacity can be fully-utilized without the “dead-space”restrictions associated with conventional disk arrays. In one embodimenta flexible storage space allocation system handles storing large andsmall file types to improve disk space utilization. In anotherembodiment an improved method for maintaining data integrity overcomesthe single drive (or double) fault limitation of conventional systems inorder to increase storage reliability while at the same time reducingmaintenance and monitoring requirements.

In one embodiment, distributed parity groups (DPG) are integrated intothe distributed file storage system technology. This architectureprovides capabilities for optimizing the use of disk resources by movingfrequently and infrequently accessed data blocks between drives so as tomaximize the throughput and capacity utilization of each drive.

In one embodiment, the architecture supports incorporation of new diskdrives without significant reconfiguration or modification of theexiting distributed file storage system to provide improved reliability,flexibility, and scalability. Additionally, the architecture permits theremoval of arbitrary disk drives from the distributed file storagesystem and automatically redistributes the contents of these drives toother available drives as necessary.

The distributed file storage system can proactively position objects forinitial load balancing, such as, for example, to determine where toplace a particular new object. Additionally, the distributed filestorage system can continue to proactively position objects, therebyaccomplishing active load balancing for the existing objects throughoutthe system. According to one embodiment, one or more filters may beapplied during initial and/or active load balancing to ensure one or asmall set of objects are not frequently transferred, or churned,throughout the resources of the system.

As used herein, load balancing can include, among other things, capacitybalancing, throughput balancing, or both. Capacity balancing seeksbalance in storage, such as the number of objects, the number ofMegabytes, or the like, stored on particular resources within thedistributed file storage system. Throughput balancing seeks balance inthe number of transactions processed, such as, the number oftransactions per second, the number of Megabytes per second, or thelike, handled by particular resources within the distributed filestorage system. According to one embodiment, the distributed filestorage system can position objects to balance capacity, throughput, orboth, between objects on a resource, between resources, between theservers of a cluster of resources, between the servers of other clustersof resources, or the like.

The distributed file storage system can comprise resources, such asservers or clusters, which can seek to balance the loading across thesystem by reviewing a collection of load balancing data from itself, oneor more of the other servers in the system, or the like. The loadbalancing data can include object file statistics, server profiles,predicted file accesses, or the like. A proactive object positionerassociated with a particular server can use the load balancing data togenerate an object positioning plan designed to move objects, replicateobjects, or both, across other resources in the system. Then, using theobject positioning plan, the resource or other resources within thedistributed file storage system can execute the plan in an efficientmanner.

According to one embodiment, each server pushes objects defined by thatserver's respective portion of the object positioning plan to the otherservers in the distributed file storage system. By employing the serversto individually push objects based on the results of their objectpositioning plan, the distributed file storage system provides aserver-, process-, and administrator-independent approach to objectpositioning, and thus load balancing, within the distributed filestorage system.

In one embodiment, the network file storage system includes a first fileserver operably connected to a network fabric; a second file serveroperably connected to the network fabric; first file system informationloaded on the first file server; and second file system informationloaded on the second file server, the first file system information andthe second file system information configured to allow a client computeroperably connected to the network fabric to locate files stored by thefirst file server and files stored by the second file server withoutprior knowledge as to which file server stores the files. In oneembodiment, the first file system information includes directoryinformation that describes a directory structure of a portion of thenetwork file system whose directories are stored on the first fileserver, the directory information includes location information for afirst file, the location information includes a server id thatidentifies at least the first file server or the second file server.

In one embodiment, the network file storage system loads first filesystem metadata on a first file server operably connected to a networkfabric; loads second file system metadata on a second file serverconnected to the network fabric, the first file system metadata and thesecond file system metadata include information to allow a clientcomputer operably connected to the network fabric to locate a filestored by the first file server or stored by the second file serverwithout prior knowledge as to which file server stores the file.

In one embodiment, the network file storage system performs a filehandle lookup on a computer network file system by: sending aroot-directory lookup request to a first file server operably connectedto a network fabric; receiving a first lookup response from the firstfile server, the first lookup response includes a server id of a secondfile server connected to the network fabric; sending a directory lookuprequest to the second file server; and receiving a file handle from thesecond file server.

In one embodiment, the network file storage system allocates space by:receiving a file allocation request in a first file server, the firstfile server owning a parent directory that is to contain a new file, thefile allocation request includes a file handle of the parent directory;determining a selected file server from a plurality of file servers;sending a file allocation request from the first server to the selectedserver; creating metadata entries for the new file in file system datamanaged by the selected file server; generating a file handle for thenew file; sending the file handle to the first file server; and creatinga directory entry for the new file in the parent directory.

In one embodiment, the network file storage system includes: a firstfile server operably connected to a network fabric; a second file serveroperably connected to the network fabric; first file system informationloaded on the first file server; and second file system informationloaded on the second file server, the first file system information andthe second file system information configured to allow a client computeroperably connected to the network fabric to locate files owned by thefirst file server and files owned by the second file server withoutprior knowledge as to which file server owns the files, the first fileserver configured to mirror at least a portion of the files owned by thesecond file server, the first file server configured to storeinformation sufficient to regenerate the second file system information,and the second file server configured to store information sufficient toregenerate the first file system information.

In one embodiment, the network file storage system: loads first filesystem metadata on a first file server operably connected to a networkfabric; loads second file system metadata on a second file serverconnected to the network fabric, the first file system metadata and thesecond file system metadata include information to allow a clientcomputer operably connected to the network fabric to locate a filestored by the first file server or stored by the second file serverwithout prior knowledge as to which file server stores the file;maintains information on the second file server to enable the secondfile server to reconstruct an information content of the first filesystem metadata; and maintains information on the first file server toenable the first file server to reconstruct an information content ofthe second file system metadata.

In one embodiment the computer network file storage system isfault-tolerant and includes: a first file server operably connected to anetwork fabric; a second file server operably connected to the networkfabric; a first disk array operably coupled to the first file server andto the second file server; a second disk array operably coupled to thefirst file server and to the second file server; first file systeminformation loaded on the first file server, the first file systeminformation including a first intent log of proposed changes to thefirst metadata; second file system information loaded on the second fileserver, the second file system information including a second intent logof proposed changes to the second metadata, the first file server havinga copy of the second intent log, the second file server maintaining acopy of the first intent log, thereby allowing the first file server toaccess files on the second disk array in the event of a failure of thesecond file server.

In one embodiment, a distributed file storage system provideshot-swapping of file servers by: loading first file system metadata on afirst file server operably connected to a network fabric, the first filesystem operably connected to a first disk drive and a second disk drive;loading second file system metadata on a second file server connected tothe network fabric, the second file system operably connected to thefirst disk drive and to the second disk drive; copying a first intentlog from the first file server to a backup intent log on the second fileserver, the first intent log providing information regarding futurechanges to information stored on the first disk drive; and using thebackup intent log to allow the second file server to make changes to theinformation stored on the first disk drive.

In one embodiment, a distributed file storage system includes: a firstfile server operably connected to a network fabric; a file systemincludes first file system information loaded on the first file server,the file system configured to create second file system information on asecond file server that comes online sometime after the first fileserver has begun servicing file requests, the file system configured toallow a requester to locate files stored by the first file server andfiles stored by the second file server without prior knowledge as towhich file server stores the files.

In one embodiment, a distributed file storage system adds servers duringongoing file system operations by: loading first file system metadata ona first file server operably connected to a network fabric; creating atleast one new file on a second file server that comes online while thefirst file server is servicing file requests, the at least one new filecreated in response to a request issued to the first file server, thedistributed file system configured to allow a requester to locate filesstored by the first file server and files stored by the second fileserver without prior knowledge as to which file server stores the files.

In one embodiment, a distributed file storage system includes: firstmetadata managed primarily by a first file server operably connected toa network fabric, the first metadata includes first file locationinformation, the first file location information includes at least oneserver id; and second metadata managed primarily by a second file serveroperably connected to the network fabric, the second metadata includessecond file location information, the second file location informationincludes at least one server identifier, the first metadata and thesecond metadata configured to allow a requestor to locate files storedby the first file server and files stored by the second file server in adirectory structure that spans the first file server and the second fileserver.

In one embodiment, a distributed file storage system stores data by:creating first file system metadata on a first file server operablyconnected to a network fabric, the first file system metadata describingat least files and directories stored by the first file server; creatingsecond file system metadata on a second file server connected to thenetwork fabric, the second file system metadata describing at leastfiles and directories stored by the second file server, the first filesystem metadata and the second file system metadata includes directoryinformation that spans the first file server and the second file server,the directory information configured to allow a requestor to find alocation of a first file catalogued in the directory information withoutprior knowledge as to a server location of the first file.

In one embodiment, a distributed file storage system balances theloading of servers and the capacity of drives associated with theservers, the file system includes: a first disk drive including a firstunused capacity; a second disk drive including a second unused capacity,wherein the second unused capacity is smaller than the first unusedcapacity; a first server configured to fill requests from clientsthrough access to at least the first disk drive; and a second serverconfigured to fill requests from clients through access to at least thesecond disk drive, and configured to select an infrequently accessedfile from the second disk drive and push the infrequently accessed filesto the first disk drive, thereby improving a balance of unused capacitybetween the first and second disk drives without substantially affectinga loading for each of the first and second servers.

In one embodiment, a distributed file storage system includes: a firstfile server operably connected to a network fabric; a second file serveroperably connected to the network fabric; first file system informationloaded on the first file server; and second file system informationloaded on the second file server, the first file system information andthe second file system information configured to allow a client computeroperably connected to the network fabric to locate files stored by thefirst file server and files stored by the second file server withoutprior knowledge as to which file server stores the files.

In one embodiment, a data engine offloads data transfer operations froma server CPU. In one embodiment, the server CPU queues data operationsto the data engine.

In one embodiment, a distributed file storage system includes: aplurality of disk drives for storing parity groups, each parity groupincludes storage blocks, the storage blocks includes one or more datablocks and a parity block associated with the one or more data blocks,each of the storage blocks stored on a separate disk drive such that notwo storage blocks from a given parity set reside on the same diskdrive, wherein file system metadata includes information to describe thenumber of data blocks in one or more parity groups.

In one embodiment, a distributed file storage system stores data by:determining a size of a parity group in response to a write request, thesize describing a number of data blocks in the parity group; arrangingat least a portion of data from the write request according to the datablocks; computing a parity block for the parity group; storing each ofthe data blocks on a separate disk drive such that no two data blocksfrom the parity group reside on the same disk drive; and storing eachthe parity block on a separate disk drive that does not contain any ofthe data blocks.

In one embodiment, a distributed file storage system includes: aplurality of disk drives for storing parity groups, each parity groupincludes storage blocks, the storage blocks includes one or more datablocks and a parity block associated with the one or more data blocks,each of the storage blocks stored on a separate disk drive such that notwo storage blocks from a given parity set reside on the same diskdrive; a redistribution module to dynamically redistribute parity groupsby combining some parity groups to improve storage efficiency.

In one embodiment, a distributed file storage system stores data by:determining a size of a parity group in response to a write request, thesize describing a number of data blocks in the parity group; arrangingat least a portion of data from the write request according to the datablocks; computing a parity block for the parity group; storing each ofthe data blocks on a separate disk drive such that no two data blocksfrom the parity group reside on the same disk drive; storing the parityblock on a separate disk drive that does not contain any of the datablocks; and redistributing the parity groups to improve storageefficiency.

In one embodiment, a distributed file storage system includes: aplurality of disk drives for storing parity groups, each parity groupincludes storage blocks, the storage blocks includes one or more datablocks and a parity block associated with the one or more data blocks,each of the storage blocks stored on a separate disk drive such that notwo storage blocks from a given parity set reside on the same diskdrive; and a recovery module to dynamically recover data lost when atleast a portion of one disk drive in the plurality of disk drivesbecomes unavailable, the recovery module configured to produce areconstructed block by using information in the remaining storage blocksof a parity set corresponding to an unavailable storage block, therecovery module further configured to split the parity groupcorresponding to an unavailable storage block into two parity groups ifthe parity group corresponding to an unavailable storage block spannedall of the drives in the plurality of disk drives.

In one embodiment, a distributed file storage system stores data by:determining a size of a parity group in response to a write request, thesize describing a number of data blocks in the parity group; arrangingat least a portion of data from the write request according to the datablocks; computing a parity block for the parity group; storing each ofthe data blocks on a separate disk drive such that no two data blocksfrom the parity group reside on the same disk drive; storing the parityblock on a separate disk drive that does not contain any of the datablocks; reconstructing lost data by using information in the remainingstorage blocks of a parity set corresponding to an unavailable storageblock to produce a reconstructed parity group; splitting thereconstructed parity group corresponding to an unavailable storage blockinto two parity groups if the reconstructed parity group is too large tobe stored on the plurality of disk drives.

In one embodiment, a distributed file storage system integrates paritygroup information into file system metadata.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other aspects, advantages, and novel features of the inventionwill become apparent upon reading the following detailed description andupon reference to the accompanying drawings:

FIG. 1 is a general overview of a distributed file storage systemshowing clients, a communication fabric, and a plurality of servers withassociated disk arrays.

FIG. 2 is a block diagram of a server node.

FIG. 3 is a block diagram of five metadata structures and connectionsbetween the five metadata structures.

FIG. 4 shows an example portion of a Filename Table.

FIG. 5 shows an example of a Gee-string stored in a Gee Table.

FIG. 6 shows one embodiment of the structure of a G-node.

FIG. 7 shows one embodiment of the structure of a Gnid-string.

FIG. 8A shows one embodiment of the structure of a Cache Node.

FIG. 8B shows a conceptual division of a Cache Node Table into threelists.

FIG. 9 shows a sample portion of a lock string.

FIG. 10 shows one embodiment of Refresh Nodes configured as a binarytree.

FIG. 11 shows one embodiment of Refresh Nodes configured as adoubly-linked list.

FIG. 12 shows one embodiment of the structure of an Intent Log Entry.

FIG. 13 shows one embodiment of the structure of a file handle.

FIG. 14A is a block diagram depicting one embodiment of a file handlelook-up process.

FIG. 14B is a block diagram depicting one embodiment of a file accessprocess.

FIG. 15 is a flow chart depicting one embodiment of performing a fileaccess.

FIG. 16 is a flow chart depicting one embodiment of performing a filehandle look-up.

FIG. 17 is a flow chart depicting one embodiment of caching file data.

FIG. 18 is a flow chart depicting one embodiment of file allocation.

FIG. 19 shows one embodiment of Super G-nodes.

FIG. 20A shows one embodiment of a Super G-node.

FIG. 20B shows one embodiment of a scheme to use Super G-nodes to holdmetadata for files of widely varying sizes.

FIG. 21 illustrates a conventional disk array that incrementally stripesdata in a RAID mapping architecture.

FIG. 22A illustrates one embodiment of a distributed file storagesystem.

FIG. 22B illustrates another embodiment of a distributed file storagesystem having built in data redundancy.

FIG. 23 illustrates a distributed file storage mechanism.

FIG. 24A illustrates a data and parity information storage method.

FIG. 24B illustrates another data and parity information storage method.

FIG. 25 illustrates another embodiment of a distributed file storagesystem having a variable capacity disk array.

FIG. 26A illustrates an embodiment of variable block number paritygroups.

FIG. 26B illustrates an embodiment of variable size parity groups.

FIG. 27 illustrates one embodiment of a G-table used to determine paritygroup mapping.

FIG. 28 illustrates a method for storing data in the distributed filestorage system.

FIG. 29 illustrates another embodiment of a G-table mapping structure.

FIG. 30 illustrates one embodiment of a fault-tolerant restorationprocess.

FIG. 31 illustrates a method for recovering corrupted or lost data inthe distributed file storage system.

FIG. 32A illustrates one embodiment of a variably sized parity groupused to store files.

FIG. 32B illustrates another embodiment of a variably sized parity groupused to store files.

FIG. 33 illustrates a data storage process used by the distributed filestorage system.

FIGS. 34A-C illustrate a parity set redistribution process.

FIG. 35A illustrates one embodiment of a parity group dissolutionprocess.

FIG. 35B illustrates one embodiment of a parity group consolidationprocess.

FIG. 36 illustrates a parity group monitoring process.

FIG. 37 illustrates a parity group optimization/de-fragmentationprocess.

FIG. 38 illustrates a load balancing method used by the distributed filestorage system.

FIG. 39 depicts a block diagram of an exemplary embodiment of serversand disk arrays of a distributed file storage system, which highlightsthe proactive object positioning of aspects of an exemplary embodimentof the invention.

FIG. 40 depicts a block diagram of an exemplary server of FIG. 39,according to aspects of an exemplary embodiment of the invention.

FIG. 41 depicts an object positioning plan for Server F3 of FIG. 39,according to aspects of an exemplary embodiment of the invention.

FIG. 42 is a block diagram of a server that provides efficientprocessing of data transfers between one or more client computers andone or more disk drives.

FIG. 43 is a block diagram of a data engine.

FIG. 44 is a map of data fields in a 64-bit data transfer instruction tothe data engine for use with a 64-bit PCI bus.

DETAILED DESCRIPTION

Introduction

As data storage requirements increase, it is desirable to be able toeasily increase the data storage capacity and/or performance of a datastorage system. That is, it is desirable to be able to increase theavailable capacity and performance of a storage system without modifyingthe configuration of the clients accessing the system. For example, in atypical Personal Computer (PC) network environment, if a databaseaccesses a network drive “M”, it is desirable to be able to add storageto this drive, all the while still calling the drive “M”, as opposed toadding, say, drives “N”, “O”, and “P” as storage requirements increase.In some cases, having to switch from a single drive “M” to four drives,“M”, “N”, “O”, “P” is a mere nuisance. However, in some cases such achange requires significant reconfiguration of client configurations. Inother cases, such a change requires modification of existing applicationsoftware, and in some instances such a change simply will not work withthe application being used.

The objective for more capacity can be met in some storage systems byadding additional disk drives to the system. However, this may notresult in increasing performance. In fact, adding additional drives maycause a significant decrease in performance. This is because: (1) ifmore ports are not added to the system when new drives are added, theperformance decreases because now more data is available (and presumablybeing accessed) through the same performance ports; and (2) thecontroller managing the file system metadata has more operations toperform and can become a bottleneck. Adding drives to existing systemsmay also limited by physical form factors. That is to say, that somesystems have physical limits to how many drives can be added.

In one embodiment, the system described herein provides a DistributedFile Storage System (DFSS) that can scale disk capacity, scale datathroughput (e.g., megabytes per second of data delivery); and scaletransaction processing throughput (e.g., processing of file systemmetadata). In one embodiment, the system also provides load balancingsuch that the scaled components handle the workload with improvedefficiency.

In one embodiment, the DFSS is dynamically distributed. In oneembodiment, the DFSS allows the integration of multiple servers so thatthe aggregation of servers appears to a client as a single storagedevice. With the DFSS, multiple servers can access and control the samedisk array, separate disk arrays, or both simultaneously. The DFSS isdesigned so that each server can continue to read and write data to thedrives it controls even when other controllers in the DFSS fail. TheDFSS also provides a mechanism for balancing the load on the controllersand the drives.

In one embodiment, the DFSS is designed such that when multiplecontrollers are controlling a single array of disk drives (also called adrive array), some or all of the servers connected to the drive arrayhave valid copies of the file system metadata describing the data onthat drive array. This means that each server has direct access to allof the file system metadata for one or more of the drive arrays it canaccess. Thus: (1) a server can continue to operate normally if the otherservers in the system fail; and (2) there is little or no performancedegradation due to one server polling another server regarding locationof data on drive arrays. The DFSS provides inter-server communication tomaintains synchronization of the file system metadata. The DFSS isdesigned such that a server can read from more than one drive array andcan read from drive arrays maintained by another server. In oneembodiment, only one controller attached to a particular drive array haswrite privileges for that particular drive array at a given time.

The DFSS maintains a description of which servers have read and writeprivileges to a file represented by a file handle passed to the client.When the client looks up a file handle, the client is informed of itsoptions regarding which servers it may read the data from (which istypically several) and which one server it needs to use to write data.In addition, since the servers typically have multiple network interfacecards (ports) to the client network, the file handle also includes datawhich suggests to the client which port is likely to be the leastutilized.

The DFSS is also designed such that when there are multiple servers,which are not sharing the same drive arrays, the drive arrays areseamlessly integrated. For example, suppose a system has 4 servers(numbered S1, S2, S3, and S4) and two drive arrays, numbered (A1, andA2). Further suppose that S1 and S2 control A1 and that S3 and S4control A2. The DFSS allows for a directory on A1 to have children onA2. In fact, the file system keeps track of usage statistics, and if A2is less utilized than A1, the file system will automatically create thenext files on A2 instead of A1. The DFSS provides coordination betweenthe servers to allow this level of integration.

Because each server has a complete set of metadata for each drive arrayit can access, a particular server can continue to operate even if otherservers fail. The DFSS includes a mechanism for determining if acontroller has failed and a mechanism for transferring write privilegesin such cases. Clearly if all controllers attached to a given drivearray fail, the data on that drive array will become inaccessible.However, the capability to support multiple controllers for each drivearray greatly reduces the likelihood of such an event. If all suchcontrollers for a drive array fail, read and write operations on theremaining controller/drive arrays continue unhindered.

The DFSS can perform load balancing at three levels. First, when adirectory lookup is performed, the file system encodes within the filehandle the lesser-used network interface to provide balancing of networkinterface resources. Second, when a new file is created, it is createdon lesser-used drives and owned by a lesser-used server. Third, dynamicanalysis of loading conditions is performed to identify under-utilizedand over-utilized drives. In response, the file system in some casesredistributes the parity groups across the drives in the existing drivearray for more optimum usage of parity checking, and in other cases thefile system moves files to lesser used drive arrays.

Many data storage systems are designed with the twin goals of providingfast access to data and providing protection against loss of data due tothe failure of physical storage media. Prior art solutions typicallyrelied on Redundant Arrays of Independent Disks (RAID). By having thedata striped across multiple drives, the data can be accessed fasterbecause the slow process of retrieving data from disk is done inparallel, with multiple drives accessing their data at the same time. Byallocating an additional disk for storing parity information, if any onedisk fails, the data in the stripe can be regenerated from the remainingdrives in the stripe.

While this approach has proven effective in many applications, it doeshave a few fundamental limitations, one of this is that there is a rigidalgorithm for mapping addresses from the file system to addresses on thedrives in the array. Hence stripes are created and maintained in a rigidmanner, according to a predetermined equation. An unfortunate sideeffect results from this limitation. There is no mechanism from keepingdata from a particular file from becoming highly fragmented, meaningthat although the data could actually fit in a single stripe, the datacould actually be located in many of stripes (this situation can beparticularly acute when multiple clients are writing to a file system).

In one embodiment, the DFSS abandons the notion of having a rigidalgorithm to map from addresses in the file system to drive addresses.Instead, DFSS uses Distributed Parity Groups (DPGs) to perform themapping. Data blocks in the DPGs are mapped via a mapping table (or alist of tables) rather than a fixed algorithm, and the blocks are linkedtogether via a table of linked lists. As discussed below, the DPGmapping can be maintained separately or can be integrated into the filesystem metadata.

Initially the mapping is somewhat arbitrary and is based on theexpectation that the drives will be accessed evenly. However, the systemkeeps track of drive usage frequency. As patterns of usage areestablished, blocks are copied from frequently accessed drives toinfrequently accessed drives. Once the copy is complete, the blocks areremapped to point to the new copies.

The disk drives are viewed as consisting of a collection of blocks. Theblock size is typically an integer multiple of the drive sector size.The drive sector size is a characteristic of the drives, and is theminimum size of data that can be written to the drives. For most FibreChannel drives, the sector size is 512 bytes.

In one embodiment, the blocks are grouped via a G-Table. The G-table isa collection of Gees, which represent the individual blocks and theirlinkage. Each Gee contains a code that identifies what that the Gee'spurpose is (e.g., linkage or representing data). Gees for a DPG strungtogether into a G-group. The entire G-table is cached, either in wholeor in part, in Random Access Memory (RAM). Individual Gees are modifiedin cache to indicate when a specific block of data is in cache. Thisprovides a straightforward way to be assured that if any client hascaused disk data to be cached, any other client seeking that same datawill be directed to the already cached data.

RAID systems are implemented independently from the file system. Thatis, from the file system's point of view, the array looks like one bigdisk. Hence stripes are created and maintained without any knowledge ofthe data they contain. Two unfortunate side effects result from thislimitation. First, there is no mechanism from keeping data from aparticular file from becoming highly fragmented, meaning that althoughthe data could actually fit in a single stripe, the data could actuallybe located many stripes (this situation can be particularly acute whenmultiple clients are writing to files). The can result in each drivedoing hundreds of seeks, while a smarter system could do just one. Thisis significant because the seek is the slowest operation related toaccessing data on disks.

Second, when a drive fails, the data on that drive must be regeneratedon a replacement drive exactly as it was on the failed drive. This meansthat if, for example, a server that has only 10% of its disk spacecurrently used, can only regenerate the data onto a replacement drive(or a hot spare) even though there is more than enough disk space toregenerate the data onto the other disks. For remote installations, if ahot spare is used, once one failure occurs, the hot spare is used andthe system can no longer tolerate another failure until the bad drive isreplaced. Of curse this could be lessened by the usage of multiple hotspares, but that significantly increases the amount of disk storage thatis not being used and merely “waiting in the wings”.

In one embodiment, the DFSS management of the DPGs is integrated intothe file system, thus making the file system “aware” of the DPGs and howdata blocks from a file are collected into parity groups. Making thefile system aware of the DPGs allows the file servers in the DFSS tomore intelligently use the disk arrays than a RAID system would. Withthe DPG system, the file system has knowledge of the drive arrays andtherefore reduces the kind of fragmenting that is typical of RAIDsystems.

Furthermore, in the event of a failure of one drive in the DFSS, thedata from the failed drive can be redistributed across the remainingdrives in a disk array. For example, suppose a file contained a DPGhaving a length (also known as a “span”) of 9 (data spread across 9drives, where 8 drives contain the data blocks and the ninth drivecontains the parity block). When one drive fails, the data can beregenerated and redistributed using a DPG of span 8. Note that withoutknowledge of which blocks are associated with which files, thisredistribution is not possible, because the file must still have thesame number of total blocks, but when the span is reduced from 9 to 8,there is an orphan block of 1 which must be still associated with thefile. This orphan is associated with another DPG in the same file. Thisassociation is not possible without knowledge of the file.Alternatively, if there are at least ten disks in the disk array, thedata can be regenerated and redistributed using a DPG span of 9,omitting the failed drive. Thus, the integration of DPG management intothe file system provides flexibility not available in a conventionalRAID system.

Sine the DFSS has full knowledge of the file system, the DFSS hasknowledge of which blocks on the disks are not used. This allows theDFSS to identify heavily used disks and redistribute data fromheavily-used disks to unused blocks on lesser-used blocks.

Storage system capability is typically measured in capacity, bandwidth,and the number of operations per second that can be processed. It isdesirable to be able to easily scale a storage system, that is, to beable to easily increase the storage capacity, the bandwidth, or theoperations per second capacity of the storage system. Storage systemcapacity is scaled by adding disk drives or to replace disk drive withdrives having greater capacity. To increase storage system bandwidth ortransactions per second capacity, it is typically necessary to addservers. It is desirable to be able to add and utilize these resourceswith little or no user intervention or configuration.

In one embodiment, the DFSS can automatically identify and utilizeavailable resources, including disk drives and servers. Two features areused realize this: 1) detecting the addition of disk drives and/orservers; and 2) a automatically initializing and incorporating newlyadded disk drives and/or servers. The same mechanisms that are used todetect newly-added resources can also be used to support the deletion ofresources.

With regard to detection of new resources, modem, high performancenetworking technologies such as Fibre Channel and Gigabit Ethernetsupply methods for determining what devices are connected to thenetwork. By storing the device map, and periodically querying thenetwork for an updated device map, the presence of new devices can bedetermined. New devices are added to the appropriate server resourcemap.

In one embodiment, a resource manager in the DFSS provides thecapability to incorporate the new resources automatically. The resourcemanager keeps track of available disk resources, as measured inavailable disk devices and the available free blocks on each disk. Theresource manager keeps track of the available servers and the unutilizedcapacity, in terms of bandwidth and transactions per second, of eachserver. When new resources are added to the DFSS, the resource managerincorporates the additions into a resource database.

The resource manager works in conjunction with aspects of the DFSS todynamically allocate storage and controller resources to files. When theDFSS needs to create a new file, or extend an already created file, itcoordinates with the resource manager to create a DPG of the appropriatesize. A similar approach is followed by the DFSS in the selection ofwhich server to use in the creation of a new file.

The resource manager approach also supports a load balancing capability.Load balancing is useful in a distributed file system to spread theworkload relatively uniformly across all of the available resources(e.g., across disks, network interfaces, and servers). The ability toproactively relocate file data is a tool that can be used to supportload balancing by moving file data from over-utilized resources tounder-utilized resources. In one embodiment, the resource managersupports load balancing by incorporating resource usage predictions.

In the DFSS, the server workload includes communication with clientmachines, reading and writing files from disks, managing file metadata,and managing server resources such as storage capacity. The workload isdivided up among the server hardware resources. If the workload isevenly divided, the resulting performance will be improved. Thus, onekey to performance is intelligent resource management. In oneembodiment, resource management involves adaptive load balancing ofserver workloads. Prior art distributed file system technologies do notoffer an effective method of performing load balancing in the face of adynamic load environment and thus cannot provide optimum performance.

In one embodiment adaptive load balancing is based on the implementationof two mechanisms. First, a mechanism is provided to predict the futureserver workload. Second, a mechanism is provided to reallocatedistributed server resources in response to the predicted workload.

Prediction of the future workload has several aspects. The first ofthese aspects is the past history of server workload, in terms if fileaccess statistics, server utilization statistics, and networkutilization statistics. The loading prediction mechanism uses thesestatistics (with an appropriate filter applied) to generate predictionsfor future loading. As a very simple example, a file that hasexperienced heavy sequential read activity in the past few minutes willlikely continue to experience heavy sequential read access for the nextfew minutes.

The predictions for future workload can be used to proactively manageresources to improve performance and capacity usage. One mechanism usedto reallocate server workload is the movement and replication of content(files) such that server and storage utilization is balanced and thedirection of client accesses to available servers is balanced. Somedegree of cooperation from client machines can be used to provide moreeffective load balancing, but client cooperation is not strictlyrequired.

A file server contains a number of hardware resources, includingcontrollers, storage elements (disks), and network elements. In theconfiguration used by the DFSS, multiple client machines are connectedthrough a (possibly redundant) client network to one or more serverclusters. Each server cluster has one or more servers and a disk storagepool.

Software resident on each server collects statistics regarding fileaccesses and server resource utilization. This includes informationregarding the access frequency, access bandwidth and access locality forthe individual files, the loading of each disk controller and diskstorage element in terms of CPU utilization, data transfer bandwidth,transactions per second, and the loading of each network element interms of network latency and data transfer bandwidth.

The collected statistics are subjected to various filter operations,which results in a prediction of future file and resource utilization(i.e., workload). This prediction can also be modified by serverconfiguration data which has been provided in advance by a systemadministrator, and explicit “hints” regarding future file and/orresource usage which can be provided directly from a client machine.

The predicted workload is then used to develop a plan that where to movecontent (files) between storage elements and where to direct clientaccesses to controllers in such a manner that the overall workload isdistributed as evenly as possible, resulting in best overall loadbalance and distributed server performance.

The predicted workload can be used to perform the following specifictypes of load balancing:

-   -   1) Client Network Load Balancing, which includes managing client        requests to the extent possible such that the client load        presented to the servers in a cluster, and the load present to        the network ports within each cluster is evenly balanced.    -   2) Intra-Cluster Storage Load Balancing, which includes of the        movement of data between the disks connected to a controller        cluster such that the disk bandwidth loading among each of the        drives in an array, and the network bandwidth among network        connecting disk arrays to servers is balanced. There are two        goals. The first goal is to achieve relatively uniform bandwidth        loading for each storage sub-network. The second goal is to        achieve relatively uniform bandwidth loading for each individual        disk drive. This is accomplished by moving relatively        infrequently accessed material to drives with frequently        accessed material.    -   3) Inter-Node Storage Load Balancing, which includes the        movement of data between drives connected to different clusters        to equalize disk access load between clusters. This is done at a        higher cost than Intra-Node Drive Load Balancing, as file data        must actually be copied between controllers over the client        network.    -   4) Intra-Node Storage Capacity Balancing, which includes        movement of data between the disks connected to a server (or        servers in a cluster) to balance disk storage utilization among        each of the drives.    -   5) Inter-Node Storage Capacity Balancing, which includes        movement of data between drives connected to different servers        to equalize overall disk storage utilization among the different        servers. This is done at a higher cost than Intra-Node Drive        Capacity Balancing, as file data must actually be copied between        controllers over the network.    -   6) File Replication Load Balancing, which includes load        balancing though file replication. This is an extension of        Inter-Node Drive Load Balancing. High usage files are replicated        so that multiple controller clusters have one or more that one        local (read-only) copy. This allows the workload associated with        these heavily-accessed files to be distributed across a larger        set of disks and servers.

Disks and servers in the DFSS can be “hot swapped” and “hot added”(meaning they can be replaced or added while the DFSS is online andservicing file requests. Disks in a disk array need not match incapacity or throughput. Extra capacity is automatically detected,configured, and used. Data is redistributed in the background (bothacross servers and across DPGs) to improve system performance. Hotadding of servers allows for increased file operations per second andfile system capacity. Hot-added servers are automatically configured andused.

In one embodiment, servers are arranged in clusters that operate asredundant groups (typically as redundant pairs). In normal operation,the servers in a cluster operate in parallel. Each acts as a primaryserver for a portion of the file system. Each server in a clustermaintains a secondary copy of the metadata and intent log of the other'sprimary file system metadata and intent log. The intent log tracksdifferences between metadata stored in memory (e.g., metadata in ametadata cache) and metadata stored on disk. Upon failure of a server inthe cluster, the server remaining server (or servers) will pick up theworkload of the failed server with no loss of metadata or transactions.

Each server in a high-performance data storage system includes storagecontroller hardware and storage controller software to manage an arrayof disk drives. Typically, a large number of disk drives are used in ahigh performance storage system, and the storage system in turn isaccessed by a large number of client machines. This places a largeworkload on the server hardware and server software. It is thereforeimportant that the servers operate in an efficient manner so that theydo not become a bottleneck in the storage system. In one embodiment, ahigh-performance data path is provided in the server so that data canefficiently be moved between the client machines and disks with aminimum amount of software intervention.

Prior art approaches for server and storage controllers tend to besoftware intensive. Specifically, a programmable CPU in the serverbecomes involved in the movement of data between the client and thedisks in the disk array. This limits the performance of the storagesystem because the server CPU becomes a bottleneck. While currentapproaches may have a certain degree of hardware acceleration, such asXOR parity operations associated with RAID, these minimal accelerationtechniques do not adequately offload the server CPU.

In one embodiment, the DFSS uses a server architecture that largelyseparates the data path from the control message path. Control messages(e.g. file read/write commands from clients) are routed to a host CPU inthe server. The host CPU processes the commands, and sets up the networkand storage interfaces as required to complete the data transferoperations associated with the commands. The data transfer operations,once scheduled with the network and storage interfaces can be completedwithout further CPU involvement, thus significantly offloading the hostCPU. In one embodiment, a data flow architecture packages instructionswith data as it flows between the network interfaces and data cachememories.

The server hardware and software perform the functions of interfacingwith client via the network interfaces, servicing client file operationrequests, setting up disk read and write operations needed to servicethese requests, and updating the file metadata as necessary to managethe files stored on disk.

The controller hardware provides a control flow path from the networkand storage interfaces to the host CPU. The host CPU is responsible forcontrolling these interfaces and dealing with the high level protocolsnecessary for client communications. The host CPU also has anon-volatile metadata cache for storing file system metadata.

A separate path for data flow is provided that connects the network andstorage interfaces with a non-volatile data cache. In one embodiment,the separate path for data flow is provided by a data engine. The datapath is used for bulk data transfer between the network and storageinterfaces. As an example of the data path operation, consider a clientfile read operation. A client read request is received on one of thenetwork interfaces and is routed to the host CPU. The host CPU validatesthe request, and determines from the request which data is desired. Therequest will typically specify a file to be read, and the particularsection of data within the file. The host CPU will use file metadata todetermine if the data is already present in the data cache memory, or ifit must be retrieved from the disks. If the data is in the data cache,the CPU will queue a transfer with the network interface to transfer thedata directly from the data cache to the requesting client, with nofurther CPU intervention required. If the data is not in the data cache,the CPU will queue one or more transfers with the storage interfaces tomove the data from disk to the data cache, again without any further CPUintervention. When the data is in the data cache, the CPU will queue atransfer on the network interface to move the data to the requestingclient, again with no further CPU intervention.

One aspect of this autonomous operation is that the CPU schedules datamovement operations by merely writing an entry onto a network or storageinterface queue. The data engine and the network and storage interfacesare connected by busses that include address and data buses. In oneembodiment, the network or storage interface does the actual datamovement (or sequence of data movements) independently of the CPU byencoding an instruction code in the address bus that connects the dataengine to the interface. The instruction code is set up by the host CPUwhen the transfer is queued, and can specify that data is to be writtenor read to one or both of the cache memories. In addition, it canspecify that an operation such as a parity XOR operation or a dataconversion operation be performed on the data while it is in transit.Because instructions are queued with the data transfers, the host CPUcan queue hundreds or thousands of instructions in advance with eachinterface, and all of these can be can be completed asynchronously andautonomously. The data flow architecture described above can also beused as a bridge between different networking protocols.

As described above, the data engine offloads the host CPU directinvolvement in the movement of data from the client to the disks andvice-versa. The data engine can be a general purpose processor, digitalsignal processor, programmable FPGA, other forms of soft or hardprogrammable logic, or a fully custom ASIC.

The data engine provides the capability for autonomous movement of databetween client network interfaces and data cache memory, and betweendisk network interfaces and cache memory. The server CPU involvement ismerely in initializing the desired transfer operations. The data enginesupports this autonomy by combining an asynchronous data flowarchitecture, a high-performance data path than can operateindependently of the server CPU data paths, and a data cache memorysubsystem. The data engine also implements the parity generationfunctions required to support a RAID-style data protection scheme.

The data engine is data-flow driven. That is, the instructions for theparallel processing elements are embedded in data packets that are fedto the data engine and to the various functional blocks within the dataengine.

In one embodiment, the data engine has four principal interfaces: twodata cache RAM interfaces, and two external bus interfaces. Otherversions of the data engine can have a different number of interfacesdepending on performance goals.

A data path exits between each network interface and each cacheinterface. In each of these data path is a processing engine thatcontrols data movement between the interfaces as well as operations thatcan be performed on the data as it moves between the interfaces. Theseprocessing engines are data-flow driven as described above.

The processing engine components that are used to perform thesefunctions include an external bus write buffer, a feedback buffer, acache read buffer, a cache write buffer, a parity engine, and theassociated controller logic that controls these elements. The bufferelements are memories of appropriate sizes that smooth the data flowbetween the external interfaces, the parity engines, and the caches.

The data engine is used to provide a data path between client networkinterface and storage network interface controllers. The networkinterface controllers may support Fibre Channel, Ethernet, Infiniband,or other high performance networking protocols. One or more host CPUsschedule network transfers by queuing the data transfer operations onthe network interfaces controllers. The network interface controllersthen communicate directly with the data engine to perform the datatransfer operations, completely autonomously from any additional CPUinvolvement. The data transfer operations may require only the movementof data, or they may combine the movement of data with other operationsthat must be performed on the data in transit.

The processing engines in the data engine can perform five principaloperations, as well as a variety of support operations. The principaloperations are: read from cache; write to cache; XOR write to cache;write to one cache with XOR write to other cache; write to both caches.

The data-flow control structure of the data engine reduces the loadingplaced on the server CPU. Once data operations are queued, the serverCPU does not need to be directly involved in the movement of data, inthe operations that are performed on data, or the management of a datatransfer.

FIG. 1 shows a general overview of a Distributed File Storage System(DFSS) 100 that operates on a computer network architecture. One or moreclients 110 operating on one or more different platforms are connectedto a plurality of servers 130, 131, 132, 133 134, 135, by way of acommunication fabric 120. In one embodiment, the communication fabric120 is a Local Area Network (LAN). In one embodiment, the communicationfabric 120 is a Wide Area Network (WAN) using a communication protocolsuch as, for example, Ethernet, Fibre Channel, Asynchronous TransferMode (ATM), or other appropriate protocol. The communication fabric 120provides a way for a client 110 to connect to one or more servers130-135.

The number of servers included in the DFSS 100 is variable. However, forthe purposes of this description, their structure, configuration, andfunctions are similar enough that the description of one server 130 isto be understood to apply to all 130-135. In the descriptions of otherelements of the figure that are similarly duplicated in the DFSS 100, adescription of one instance of an element is similarly to be understoodto apply to all instances.

The server 130 is connected to a disk array 140 that stores a portion ofthe files of the distributed file storage system. Together, theserver-disk array pair 130, 140 can be considered to be one server node150. The disks in the disk array 140 can be Integrated Drive Electronics(IDE) disks, Fibre Channel disks, Small Computer Systems Interface(SCSI) disks, InfiniBand disks, etc. The present disclosure refers todisks in the disk array 140 by way of example and not by way oflimitation. Thus, for example the “disks” can be many types ofinformation storage devices, including, for example, disk drives, tapedrives, backup devices, memories, other computers, computer networks,etc.

In one embodiment, one or more server nodes 150, 151 are grouped into acluster 160 of server nodes. In one embodiment, each server 130 in thecluster 160 is connected not only to its own disk array 140, but also tothe disk array(s) 141 of the other server(s) 131 of the cluster 160.Among other advantages conferred by this redundant connection is theprovision of alternate server paths for reading a popular file or a fileon a busy server node. Additionally, allowing servers 130, 131 to accessall disk arrays 140, 141 of a cluster 160 provides the assurance that ifone server 130 of a cluster 160 should fail, access to the files on itsassociated disk array 140 is not lost, but can be provided seamlessly bythe other servers 131 of the cluster 160.

In one embodiment, files that are stored on the disk array 140 of oneserver node 150 are mirrored on the disk array(s) 141 of each servernode 151 in the cluster 160. In such an embodiment, if the disk array140 should become unusable, the associated server 130 will still be ableto access copies of its files on the other disk array(s) 141 of thecluster 160.

As shown in FIG. 1, the server 130 is associated with the disk array 140that can include multiple disk drives of various sizes and capacities.Thus, the DFSS 100 allows for much more flexibility than manyconventional multi-disk file storage systems that require strictconformity amongst the disk arrays of the system. Among other advantagesconferred by this flexibility is the ability to upgrade portions of thesystem hardware without having to upgrade all portions uniformly andsimultaneously.

In many conventional networked storage systems, a user on a client needsto know and to specify the server that holds a desired file. In the DFSS100 described in FIG. 1, although the files of the file system can bedistributed across a plurality of server nodes, this distribution doesnot require a user on a client system 110 to know a priori which serverhas a given file. That is, to a user, it appears as if all files of thesystem 100 exist on a single server. One advantage of this type ofsystem is that new clusters 160 and/or server nodes 150 can be added tothe DFSS 100 while still maintaining the appearance of a single filesystem.

FIG. 2 is a block diagram showing one embodiment 200 of the server node150 in the DFSS 100. As in FIG. 1, the server node 150 includes theserver 130 and the disk array 140 or other data storage device.

The server 130 includes a server software module 205. The serversoftware module 205 includes server interface (SI) software 240 forhandling communications to and from clients 110, file system (FS)software 250 for managing access, storage, and manipulation of thefiles, and a JBOD (Just a Bunch of Disks) interface (JI) 260 forhandling communications with the disk array 140 and with other diskarrays of the cluster 160. Communications between the server interface240 and the file system 250 take place using a Client Server Object 245.Communications between the file system 250 and the JBOD interface 260take place using a Disk Service Object 255. In one embodiment, asdepicted in FIG. 2, the software of the file system 250 residesprincipally on the servers 130, 131, while the file data is stored onstandard persistent storage on the disk arrays 140, 141 of the DFSS 100.

The server software module 205 also includes a polling module 270 forpolling clients 110 of the DFSS 100 and a polling module 280 for pollingdisk arrays 140 of the DFSS 100.

In the embodiment 200 shown in FIG. 2, the server 130 includes a FibreChannel Application Programming Interface (FC-API) 210 with two FibreChannel ports 211 for communicating via the fabric 120 with the client110 and with other server(s) 151 of the cluster 160. The FC-API 210 alsocommunicates with the server interface 240 and with the client pollingmodule 270 in the server software module 205.

The server 130 includes an FC-API 220 with two Fibre Channel ports 221for communicating with the disk array 140 and with other disk arrays ofits cluster 160. The FC-API 220 may communicate with the disk array 140via a communication fabric 222, as shown in FIG. 2. The FC-API 220 mayalso communicate with the disk array 140 directly. The FC-API 220 alsocommunicates with the JBOD interface 260 and with the disk pollingmodule 280 in the server software module 205.

The server 130 includes an Ethernet interface 230 with two Ethernetports 231, 232 configured to handle Gigabit Ethernet or 10/100TEthernet. The Ethernet interface 230 communicates with the serverinterface 240 in the server software module 205. In FIG. 2, the GigabitEthernet port 231 communicates with one or more Ethernet clients 285 ofthe DFSS 100. The Ethernet clients 285 include an installable clientinterface software component 286 that communicates with the client'soperating system and with the Ethernet interface 230 of the server node150. In FIG. 2, the Ethernet port 232 communicates with anadministrative interface system 290.

To improve performance for certain implementations, a small file systemsoftware layer may also exist on clients 110, as shown in the embodiment200 shown in FIG. 2, where the client system 110 includes an installablesoftware component called the Client Interface (CI) 201 thatcommunicates with both the client's operating system and, via thecommunication fabric 120, with a server node 150 of the DFSS 100.

The functions of the FC-API modules 210, 220 and the Ethernet interface230 may alternatively be handled by other communication protocols.

Overview of Metadata Structures

In order to perform normal file system operations, such as, for example,creating and deleting files, allowing clients to read and write files,caching file data, and keeping track of file permissions, while alsoproviding the flexibility mentioned above, a cluster 160 maintainsmetadata about the files stored on its disk arrays 140, 141. Themetadata comprises information about file attributes, file directorystructures, physical storage locations of the file data, administrativeinformation regarding the files, as well as other types of information.In various embodiments, the file metadata can be stored in a variety ofdata structures that are configured in a variety of interconnectedconfigurations, without departing from the spirit of the distributedfile system. FIG. 3 is a block diagram that shows one embodiment of aconfiguration comprising five metadata structures and connectionsbetween them. Each of these structures, the data they hold, and how thestructures are used are described in greater detail below.

Referring to FIG. 3, a Filename Table 310 includes a collection offilenames for both files stored on the server node 150 as well as filesthat are children of directories stored on the server node 150.

A G-node Table 330 includes a collection of G-nodes, where each G-nodecontains data related to attributes of a file. A one-to-onecorrespondence exists between the G-nodes and files stored on the servernode 150.

A Gee Table 320 holds data about the physical locations of the fileblocks on the disk array 140. The Gee Table 320 additionally includespointers to each associated G-node in the G-node Table 330, and eachG-node in the G-node Table 330 includes a pointer to an associatedportion of the Gee Table 320.

A Gnid Table 340 on the server node 150 includes Gnid-strings that holddata describing the directory structure of that portion of the filesystem 250 whose directories are stored on the server node 150. Aone-to-one correspondence exists between the Gnid-strings and directoryfiles stored on the server node 150. Gnid-strings are collections ofGnids, which hold information about individual files that exist within agiven directory. The file system 250 allows files within a directory tobe stored on a cluster that is different from the cluster on which theparent directory is stored. Therefore, Gnids within a Gnid-string on theserver node 150 can represent files that are stored on clusters otherthan the current cluster 160.

Each Gnid includes several pointers. A Gnid in the Gnid Table 340includes a pointer to an associated filename for the file represented bythe Gnid. Because the Filename Table 310 includes filenames for bothfiles stored on the server node 150 as well as files that are childrenof directories stored on the server node 150, all Gnids on the servernode 150 point to the Filename Table 310 on the server node 150.

A Gnid in the Gnid Table 340 includes a pointer to its parentdirectory's G-node in the G-node Table 330, and a parent directory'sG-node includes a pointer to the beginning of its associated Gnid-stringin the Gnid Table 340.

Each Gnid also includes a pointer to its own G-node. Since a Gnid canrepresent a file that is stored on another cluster 160 of the filesystem 250, a pointer to the Gnid's own G-node can point to the G-nodeTable 330 on another server node of the file system 250.

A Cache Node Table 350 includes the Cache Nodes that hold informationabout the physical locations of file blocks that have been cached,including a pointer to a cache location as well as a pointer to anon-volatile location of the data on the disk array 140. A pointer to aCache Node exists in the Gee Table 320 for every associated data blockthat has been cached. Similarly, a pointer exists in the Cache Node to alocation in the Gee Table 320 associated with a disk storage locationfor an associated data block.

Mirroring of Metadata Structures

To review the description from FIG. 1, in one embodiment, the servers130, 131 of a cluster 160 are able to access files stored on all thedisk array(s) 140, 141 of the cluster 160. In one embodiment, all servernodes 150, 151 of a cluster 160 have copies of the same Filename Table310, Gee Table 320, G-node Table 330, and Gnid Table 340.

In embodiments where files, as well as metadata, are mirrored across theserver nodes 150, 151 of a cluster 160, a different Gee Table 320 existsfor each disk array 140, 141 within a cluster 160, since the Gee Table320 holds information about the physical storage locations of the fileson a given disk array, and since the disk arrays 140, 141 within a givencluster 160 are not constrained to being identical in capacity orconfiguration. In such an embodiment, the servers 130, 131 within thecluster 160 have copies of both the Gee Table 320 for a first disk array140 and the Gee Table 320 for each additional disk array 141 of thecluster.

In one embodiment, in order to enhance both the security of the metadataand efficient access to the metadata, each server node 150, 151 stores acopy of the Filename Table 310, the G-node Table 330, the Gnid Table340, and the Gee Table 320 in both non-volatile memory (for security)and in volatile memory (for fast access). Changes made to the volatileversions of the metadata structures 310, 320, 330, 340 are periodicallysent to the non-volatile versions for update.

In one embodiment, the server nodes 150, 151 in the cluster 160 do nothave access to one another's cache memory. Therefore, unlike the fourmetadata structures 310, 320, 330, and 340 already described, the CacheNode Table 350 is not replicated across the server nodes 150, 151 of thecluster 160. Instead, the Cache Node Table 350 stored in volatile memoryon a first server 130 refers to the file blocks cached on the first theserver 130, and the Cache Node Table 350 stored in volatile memory on asecond server 131 refers to file blocks cached on the second server 131.

Division of Metadata Ownership

In one embodiment, the metadata structures described in FIGS. 3 areduplicated across the server nodes 150, 151 of the cluster 160, allowingaccess to a set of shared files and associated metadata to all serversin the cluster 160. All of the server nodes 150, 151 in the cluster 160can access the files stored within the cluster 160, and all areconsidered to be “owners” of the files. Various schemes can be employedin order to prevent two or more servers 130, 131 from altering the samefile simultaneously. For example, in embodiments where the cluster 160includes two server nodes 150 and 151, one such scheme is toconceptually divide each of the duplicated metadata structures in halfand to assign write privileges (or “primary ownership”) for one half ofeach structure to each server node 150, 151 of the cluster 160. Only theserver node 150 that that is primary owner of the metadata for aparticular file has write privileges for the file. The other servernode(s) 151 of the cluster 160 are known as “secondary owners” of thefile, and they are allowed to access the file for read operations.

In a failure situation, when the server 130 determines that itscounterpart 131 is not functional, the server 130 can assume primaryownership of all portions of the metadata structures 310, 320, 330, 340and all associated files owned by the server 131, thus allowingoperation of the file system 250 to continue without interruption. Inone embodiment, if a server in cluster 160 having more than two serversexperiences a failure, then primary ownership of the failed server'sfiles and metadata can be divided amongst the remaining servers of thecluster.

Filename Table

FIG. 4 shows a sample portion of the Filename Table 310. In oneembodiment, the Filename Table 310 on the server 130 contains FilenameEntries 410, 420, 430, 440 for files which are either stored in the diskarray 140 or are parented by a directory file in the disk array 140. Inone embodiment, the Filename Table 310 is stored as an array. In FIG. 4,a ‘Start of String’ (SOS) marker 411 marks the beginning of the FilenameEntry 410, and a character string 414 holds characters of the filename,“Doe.” In one embodiment, a checksum 412 for the string 414 is alsoincluded in the Filename Entry 410. In one embodiment, a filename lengthcount 413 representing the length of the string 414, shown in FIG. 4 tohave a value of “3,” is included in the Filename Entry 410. The checksum412 and the filename length count 413 advantageously allow for anexpedited search of the Filename Table 310.

A ‘Start of String’ (SOS) marker 421 marks the beginning of the FilenameEntry 420 with a checksum 422, a filename length count 423 of “6,” and acharacter string 424 holding the filename “Thomas.”

A ‘Deleted String’ (DS) marker 431 marks the beginning of the FilenameEntry 430 with a checksum 432, a filename length count 433 of “4,” and acharacter string 434 holding the filename “Frog.”

A ‘Start of String’ (SOS) marker 441 marks the beginning of the FilenameEntry 440 with a checksum 442, a filename length count 443 of “2,” and acharacter string 444 holding the filename “It.”

Comparing the checksums 412, 422, 432, 442 and the filename lengthcounts 413, 423, 433, 443 of each Filename Entry 410, 420, 430, 440 tothose calculated for a desired filename provides a quick way toeliminate most Filename Entries in the Filename Table 310 before havingto make a character-by-character comparison of the character strings414, 424, 434, 444.

Another advantage of including the filename length counts 413, 423, 433,443 applies when deleting a Filename Entry 410, 420, 430, 440 from theFilename Table 310. Replacing the ‘Start of String’ (SOS) marker 411,421, 441 with a ‘Deleted String’ (DS) marker 431, as in the FilenameEntry 430, signals that the corresponding file is no longer stored onthe disk array 140, even if the remainder of the Filename Entry 432-434remains unchanged. The filename length 433 accurately represents thelength of the “deleted” string 434, and when a new filename of the samelength (or shorter) is to be added to the table 310, the new name andchecksum (and filename length count, if necessary) can be added into theslot left by the previous filename.

Gee Table

The file system 250 divides files into one or more file logical blocksfor storage. Each file logical block is stored in a cluster of one ormore disk logical blocks on the disk array 140. Although the file system250 retains many of the advantages of a conventional file systemimplemented on RAID (Redundant Array of Independent Disks), includingthe distribution of files across multiple disk drives and the use ofparity blocks to enhance error checking and error correcting, unlikemany RAID systems, the file system 250 does not restrict file logicalblocks to one uniform size. File logical blocks of data and paritylogical blocks can be the size of any integer multiple of a disk logicalblock. This variability of file logical block size allows forflexibility in allocating disk space and, thus, for optimized use ofsystem resources.

In the file system 250, the size of a file logical block is described byits integer multiple, called its extent, in disk logical blocks. Forexample, a file logical block with an extent of 3 is stored in a clusterof 3 disk logical blocks on the disk array 140.

The Gee Table 320 stores metadata describing the disk logical blocklocations on the disk array 140 for each file logical block of thefiles.

FIG. 5 shows one embodiment of a Gee Table 320 that is implemented as aflat array. Each indexed row 510-529 of the Gee Table 320 is called aGee. In FIG. 5, Gees 510-528 relate to a single file that is dividedinto ten file logical blocks. Such a set of Gees 510-528, which togetherdescribe the logical location of a single file on the disk array 140, isknown as a Gee-string 500. A Gee-string is made up of one or moreGee-groups. Each Gee-group is a set of contiguous Gees that all relateto a single file. In FIG. 5, the Gee-string 500 includes threeGee-groups, 550, 551, and 552. The Gee 529 relates to a separate file,as will be explained in more detail below.

In one embodiment, the Gees 510-529 include a G-code field 590 and aData field 591. The G-code field 590 in the Gees 510-529 indicates thetype of data that is included in the Data field 591. In FIG. 5, fourtypes of G-codes 590 are depicted: “G-NODE,” “DATA,” “PARITY,” and“LINK.”

In one embodiment, the G-code 590 of “G-NODE” indicates that the Gee isa first Gee of a Gee-group. For example, the first Gee of the Gee-group550 is a G-NODE Gee 510. Similarly, the first Gee of the Gee-groups 551and 552 are also G-NODE Gees 520, 525.

The Data field 591 of a G-NODE Gee can include a pointer to the file'sG-node in the G-node Table 330 and information about whether this is thefirst (or Root) G-NODE Gee of the file's Gee-string 500. The Data field591 of a G-NODE Gee can also include information about the extent, orsize, of the logical disk block clusters for the file logical blocks ofthe Gee-group, as will be described in greater detail below.

In FIG. 5, the Data fields 591 of the G-NODE Gees 510, 520, and 525contain a reference to G-node index “67,” indicating that they allrelate to the file associated with the G-node at index “67” of theG-node Table 330. That is, they all relate to portions of the same file.The Data field 591 of the Gee 529 refers to the G-node index “43,”indicating that it relates to a different file.

Of the G-NODE Gees 510, 520, 525, only the first Gee 510 contains anindication that it is a Root Gee, meaning that it is the first Gee ofthe Gee-string 500. The Gee 529 is a G-NODE Gee, indicating that it is afirst Gee of a Gee-group (the remainder of which is not shown), and theData field 591 of the Gee 529 also indicates that the Gee 529 is not aRoot Gee for its Gee-string.

Following the G-NODE Gee in a Gee-group are Gees representing one ormore Distributed Parity Groups (DPGs) 560, 561, 52, 563. A DPG is set ofone or more contiguous DATA Gees followed by an associated PARITY Gee. ADATA Gee is a Gee with a G-code 590 of “DATA” that lists disk logicalblock(s) where a file logical block is stored. For example, in FIG. 5,the Gees 511-513, 515-517, 521-522, and 526-527 are all DATA Gees, andeach is associated with one file logical block 592.

A PARITY Gee is a Gee with a G-code 590 of “PARITY.” Each PARITY Geelists disk logical block location(s) for a special type of file logicalblock that contains redundant parity data used for error checking anderror correcting one or more associated file logical blocks. A PARITYGee is associated with the contiguous DATA Gees that immediately precedethe PARITY Gee. A set of contiguous DATA Gees and the PARITY Gee thatfollows them are known collectively as a Distributed Parity Group 560,561, 562, 563.

For example, in FIG. 5, the PARITY Gee 514 is associated with the DATAGees 510-513, and together they form the Distributed Parity Group 560.Similarly, the PARITY Gee 518 is associated with the DATA Gees 515-517,and together they form the Distributed Parity Group 561. The PARITY Gee523 is associated with the DATA Gees 521-522, which together form theDistributed Parity Group 562, and the PARITY Gee 528 is associated withthe DATA Gees 526-527, which together form the Distributed Parity Group563.

The size of a disk logical block cluster described by a DATA Gee or aPARITY Gee, as measured in number of disk logical blocks, matches theextent listed in the previous G-NODE Gee. In the example of FIG. 5, theG-NODE Gee 510 defines an extent size of 2, and each DATA and PARITY Gee511-518 of the two Distributed Parity Groups 560, 561 of the Gee-group550 lists two disk logical block locations. Similarly, G-NODE Gee 520 ofthe second Gee-group 551 defines an extent size of 3, and each DATA andPARITY Gee 521-523 of the Gee-group 551 lists three disk logical blocklocations. G-NODE Gee 525 of the third Gee-group 552 defines an extentsize of 3, and each DATA and PARITY Gee 526-528 of the Gee-group 552lists three disk logical block locations.

If a Gee-group is not the last Gee-group in its Gee-string, then amechanism exists to logically link the last Gee in the Gee-group to thenext Gee-group of the Gee-string. LINK Gees 519, 524 have the G-code 590of “LINK” and a listing in their respective Data fields 591 thatprovides the index of the next Gee-group of the Gee-string 500. Forexample, the Gee 519 is the last Gee of Gee-group 550, and its Datafield 591 includes the starting index “76” of the next Gee-group 551 ofthe Gee-string 500. The Gee 524 is the last Gee of Gee-group 551, andits Data field 591 includes the starting index “88” of the nextGee-group 552 of the Gee-string 500. Since the Gee-group 552 does notinclude a LINK Gee, it is understood that Gee-group 552 is the lastGee-group of the Gee-string 500.

A G-code 590 of “FREE” (not shown in FIG. 5) indicates that the Gee hasnever yet been allocated and has not been associated with any disklogical location(s) for storing a file logical block. A G-code 590 of“AVAIL” (not shown in FIG. 5) indicates that the Gee has been previouslyallocated to a cluster of disk logical block(s) for storing a filelogical block, but that the Gee is now free to accept a new assignment.Two situations in which a Gee is assigned the G-code of “AVAIL” are:after the deletion of the associated file logical block; and aftertransfer of the file to another server in order to optimize load balancefor the file system 250.

A G-code of “CACHE DATA” indicates that the disk logical block clusterassociated with the Gee (which was previously a DATA Gee) has beencached. A G-code of “CACHE PARITY” indicates that the disk logical blockcluster associated with this Gee (which was previously a PARITY Gee) hasbeen cached. The CACHE DATA and CACHE PARITY G-codes will be describedin greater detail when Cache Nodes and the Cache Node Table aredescribed in connection with FIG. 8A below.

G-node Table

The G-node Table 330 is a collection of G-nodes, where each G-nodeincludes attribute information relating to one file. Attributeinformation can include, but is not restricted to: information aboutphysical properties of the file (such as, for example, its size andphysical location on disk); information about the file's relationshipsto other files and systems (such as, for example, permissions associatedwith the file and server identification numbers for the primary andsecondary owners of the file); and information about access patternsassociated with the file (such as, for example, time of the last fileaccess and time of the last file modification).

In addition to file attribute information, a G-node provides links tothe root Gee and a midpoint Gee of the file's Gee-string in the GeeTable 320. If the file is a directory file, its G-node also contains apointer to the beginning of the Gnid-string that describes the filescontained in the directory, as will be explained with reference to FIG.7 below.

In one embodiment, the G-node Table 330 is implemented as a flat array.

FIG. 6 shows one embodiment of information that can be included in aG-node 600. A File Attribute-type field 602 designates a file asbelonging to a supported file type. For example, in one embodiment,NFNON indicates that the G-node is not currently associated with a file,NFREG indicates that the associated file is a regular file, NFDIRindicates that the associated file is a directory, NFLINK indicates thatan associated file is a symbolic link that points to another file.

A File Attribute-mode field 604 gives information regarding accesspermissions for the file.

A File Attribute-links field 606 designates the number of directoryentries for a file in the file system 250. This number can be greaterthan one if the file is the child of more than one directory, or if thefile is known by different names within the same directory.

A File Attribute-uid field 608 designates a user ID for a file'suser/owner.

A File Attribute-gid field 610 designates a group ID of a file'suser/owner.

A File Attribute-size field 612 designates a size in bytes of a givenfile.

A File Attribute-used field 614 designates an amount of disk space usedby a file.

A File Attribute-fileId field 620 designates a file ID.

A File Attribute-atime field 622 designates the time of the last accessto the file.

A File Attribute-mtime field 624 designates the time of the lastmodification to the file.

A File Attribute-ctime field 626 designates the time of the lastmodification to a G-node (excluding updates to the atime field 622 andto the mtime field 624).

If a file is a directory file rather than a data file, then its ChildGnid Index field 628 is an index for the oldest child in an associatedGnid-string (to be described in greater detail with reference to FIG. 7below); otherwise, this field is not used.

A Gee Index-Last Used field 630 and a Gee Offset-Last Used field 631together designate a location of a most recently accessed Gee 510 for agiven file. These attributes can be used to expedite sequential readingof blocks of a file.

A Gee Index-Midpoint field 632 and a Gee Offset-Midpoint field 633together point to a middle Gee 510 of the Gee-string 500. Searching fora Gee for a given file block can be expedited using these two fields inthe following way: if a desired block number is greater than the blocknumber of the midpoint Gee, then sequential searching can begin at themidpoint of the Gee-string 500 rather than at its beginning.

A Gee Index-Tail field 634 and a Gee Offset-Tail field 635 togetherpoint to the last Gee 528 of the Gee-string 500. New data can easily beappended to the end of a file using the pointers 634 and 635.

A Gee Index-Root field 636 is an index of the root Gee 510 of aGee-string for an associated file.

A G-node Status field 638 indicates whether the G-node is being used oris free for allocation.

A Quick Shot Status field 640 and a Quick Shot Link field 642 are usedwhen a “snapshot” of the file system 250 is taken to allow for onlineupdates and/or verification of the system that does not interrupt clientaccess to the files. During a “snapshot,” copies of some portions of thesystem are made in order to keep a record of the system's state at onepoint in time, without interfering with the operation of the system. Insome embodiments, more than one Quickshot can be maintained at a giventime. The Quick Shot Status field 640 indicates whether the G-node wasin use at the time of the “snapshot” and, therefore, if it has beenincluded in the “snapshot.” If the G-node has been included in the“snapshot,” the Quick Shot Link field 642 provides a link to the newlyallocated copy of the G-node.

In one embodiment, a bit-mask is associated with each element with thefile system 250 identifying any of a number of Quickshot instances towhich the element belongs. When a Quickshot is requested, a task can setthe bit for every element, holding the file system at bay for a minimumamount of time. Thus, capturing the state of a file system comprisesidentifying elements in the file system as being protected, rather thanactually copying any elements at the time of the Quickshot.

In one embodiment, the file system uses a copy-on-write mechanism sothat data is not overwritten; new blocks are used for new data, and themetadata is updated to point to the new data. Thus, a minimum ofoverhead is required to maintain a Quickshot. If a block is beingwritten and the file system element being modified has a bit setindicating that it is protected by a Quickshot, the metadata is copiedto provide a Quickshot version of the metadata, which is distinct fromthe main operating system. Then, the write operation continues normally.

Gnid Table

Files in the file system 250 are distributed across a plurality ofserver nodes 150 while still appearing to clients 110 as a single filesystem. According to different embodiments, files can be distributed ina variety of ways. Files can be distributed randomly, or according to afixed distribution algorithm, or in a manner that enhances loadbalancing across the system, or in other ways.

In one embodiment, the files of a given directory need not be storedphysically within the same cluster as the cluster that stores thedirectory file itself. Nor does one large table or other data structureexist which contains all directory structure information for the entirefile system 250. Instead, directory structure information is distributedthroughout the file system 250, and each server node 150 is responsiblefor storing information about the directories that it stores and aboutthe child files of those directories.

In one embodiment, server nodes of the DFSS 100 hold directory structureinformation for only the directory files that are stored on the servernode and for the child files of those directories, that is, the filesone level down from the parent directory. In another embodiment, servernodes of the DFSS 100 hold directory structure information for eachdirectory file stored on the server node and for files from a specifiednumber of additional levels below the parent directory in the filesystem's directory structure.

In one embodiment, an exception to the division of responsibilitydescribed above is made for the directory structure information for a“root” directory of the file system 250. The “root” directory is adirectory that contains every directory as a sub-directory and, thus,every file in the file system 250. In this case, every server in thefile system 250 can have a copy of the directory structure informationfor the “root” directory as well as for its own directories, so that asearch for any file of unknown location can be initiated at the “root”directory level by any server of the file system 250. In anotherembodiment, the directory structure information for the “root” directoryis stored only in the cluster that stores the “root” directory, andother clusters include only a pointer to the “root” directory.

The Gnid Table 340 on the server node 150 defines a structure fordirectory files that reside on the server node 150. The Gnid Table 340comprises Gnid-strings, which, in one embodiment, are linked listsimplemented within a flat array. In one embodiment, a Gnid-string existsfor each directory file on the server node 150. Individual elements of aGnid-string are called Gnids, and a Gnid represents a child file of agiven parent directory.

FIG. 7 shows the structure of one embodiment of a Gnid-string 700. Inthis embodiment, the Gnid-string 700 for a directory file is a linkedlist of Gnids 710-713, where each Gnid represents one file in thedirectory. In one embodiment, in order to expedite searching theGnid-string 700 for a given Gnid, the Gnids are kept in ascending orderof the checksums 412, 422, 442 of the files' filenames 410, 420, 440,such that the Gnid with the smallest checksum is first in theGnid-string 700. When a new file is added to a directory, a Gnid for thenewly added file is inserted into the appropriate location in theGnid-string 700. Search algorithms that increase the efficiency of asearch can exploit this sorted arrangement of Gnids 710-713 within aGnid-string 700.

Since Gnids share a common structure, a description of one Gnid 710 isto be understood to describe the structure of all other Gnids 711-713 aswell.

The Gnid 710 includes, but is not restricted to, seven fields 720, 730,740, 750, 760, 770, and 780. A Status field 720 indicates whether theGnid 710 is a first Gnid (GNID_OLDEST) in the Gnid-string 700, a lastGnid (GNID_YOUNGEST) in the Gnid-string 700, a Gnid that is neitherfirst nor last (GNID_SIBLING) in the Gnid-string 700, or a Gnid that isnot currently in use (GNID_FREE).

A Parent G-node Ptr field 730 is a pointer to the G-node for the file'sparent directory in the G-node Table 330.

A Sibling Gnid Ptr field 740 is a pointer to the next Gnid 711 on theGnid-string 700. In the embodiment described above, the Sibling Gnid Ptrfield 740 points to the Gnid within the Gnid-string 700 that has thenext largest checksum 412, 422, 442 value. A NULL value for the SiblingGnid Ptr field 740 indicates that the Gnid is the last Gnid of theGnid-string 700.

A G-node Ptr field 750 is a pointer to the file's G-node 600, indicatingboth the server node that is primary owner of the file and the file'sindex into the G-node Table 330 on that server node.

A Filename Ptr field 760 is a pointer to the file's Filename Entry inthe Filename Table 310.

A ForBiGnid Ptr field 770 is a pointer used for skipping ahead in theGnid-string 700, and a BckBiGnid Ptr field 780 is a pointer for skippingbackward in the Gnid-string 700. In one embodiment, the fields 770 and780 can be used to link the Gnids into a binary tree structure, or oneof its variants, also based on checksum size, thus allowing for fastsearching of the Gnid-string 700.

Cache Node Table

The Cache Node Table 350 stores metadata regarding which data blocks arecurrently cached as well as which data blocks have been most recentlyaccessed. The Cache Node Table 350 is integrated with the file system250 by way of a special type of Gee 510 in the Gee Table 320. When adata block is cached, a copy of its associated DATA Gee 511-513,515-517, 521-522, 526-527, which describes the location of the data onthe disk array 140, is sent to the Cache Node Table 350, where it isheld until the associated data is released from the cache. Meanwhile,the DATA Gee 511-513, 515-517, 521-522, 526-527 in the Gee Table 320 ismodified to become a CACHE DATA Gee; its G-Code 590 is changed from DATAto CACHE DATA, and instead of listing a data block's location on disk140, the Data field 591 of the Gee now indicates a location in the CacheNode Table 350 where a copy of the original DATA Gee 511-513, 515-517,521-522, 526-527 was sent and where information about the data block'scurrent location in cache can be found.

In one embodiment, the Cache Node Table 350 is implemented as a list offixed length Cache Nodes, where a Cache Node is associated with each Gee511-513, 515-517, 521-522, 526-527 whose data has been cached. Thestructure of one embodiment of a Cache Node 800 is described in FIG. 8A.

Referring to FIG. 8A, the Cache Node 800 is shown to include ninefields. A Data Gee field 810 is a copy of the DATA Gee 511-513, 515-517,521-522, 526-527 from the Gee Table 320 that allows disk locationinformation to be copied back into the Gee Table 320 when the associateddata block is released from cache. A PrevPtr field 815 holds a pointerto the previous Cache Node in the Cache Node Table 350. A NextPtr field820 holds a pointer to the next Cache Node in the Cache Node Table 350.In one embodiment, the Cache Node Table 350 is implemented as a flatarray, in which case the PrevPtr 815 and NextPtr 820 fields can holdindices of a previous and a next item in the table. A CacheBlockAddrfield 825 holds a pointer to a location in cache where the associateddata has been cached. A ReadCt field 830 is a counter of the number ofclients currently reading the associated data block. A CacheTime field835 holds a time that the associated cache contents were last updated. ARegenerated field 840 holds a flag indicating that the associated cachecontents have been regenerated. A CacheBlockHiAddr field 845 and aCacheBlockLoAddr field 850 hold a “high water mark” and “low water mark”of the data in a cache block. These “water marks” can be used todemarcate a range of bytes within a cache block so that if a writeoperation has been performed on a subset of a cache block's bytes, thenwhen the new data is being written to disk, it is possible to copy onlyrelevant or necessary bytes to the disk.

In one embodiment, the Cache Node Table 350 is conceptually divided intothree lists, as depicted in FIG. 8B. A Normal List 860 includes all theCache Nodes 800 in the Cache Node Table 350 which are associated withcached data that is not currently in use. A Write List 865 holds theCache Nodes 800 of data blocks that have been modified and that arewaiting to be written to disk. A Read List 870 holds the Cache Nodes 800of data blocks that are currently being read by one or more clients.

When existing cached data is needed for a write or a read operation, theassociated Cache Node 800 can be “removed” from the Normal List 860 and“linked” to the Write List 865 or the Read List 870, as appropriate. TheCache Nodes 800 in each of the lists 860, 865, 870 can be linked byusing the PrevPtr 815 and NextPtr 820 fields. The Cache Nodes 800 ofdata blocks that are being written to can be “moved” from the NormalList 860 to the Write List 865 until an associated data block stored onthe disk array 140 is updated. The Cache Nodes 800 of data blocks thatare being read can be similarly “moved” to the Read list by resettingthe links of the PrevPtr 815 and NextPtr 820 fields.

The Cache Nodes 800 of data blocks that are being read can additionallyhave their ReadCt field 830 incremented, so that a count may be kept ofthe number of clients currently reading a given data block. Ifadditional clients simultaneously read the same file, the server 130increments the Cache Node's ReadCt field 830 and the Cache Node 800 canstay in the Read List 870. As each client finishes reading, the ReadCt830 is appropriately decremented. When all clients have finished readingthe file block and the ReadCt field 830 has been decremented back to astarting value, such as 0, then the Cache Node 800 is returned to theNormal List 860.

In one embodiment, the server 130 that wishes to access an existingCache Node 800 for a read or a write operation can “take” the desiredCache Node 800 from any position in the Normal List 860, as needed. TheCache Nodes 800 from the Write List 865 whose associated data havealready been written to disk are returned to a “top” position 875 of theNormal List 860. Similarly, when no clients are currently reading thecached data associated with a given the Cache Node 800 on the Read List870, the Cache Node 800 is returned to the “top” position 875 of theNormal List 860. In this way, a most recently accessed Cache Node 800amongst the Cache Nodes 800 on the Normal List 860 will be at the “top”position 875, and a least recently accessed the Cache Node 800 will beat a “bottom” position 880.

In one embodiment, if space in the cache is needed for a new data blockwhen all of the Cache Nodes 800 have been assigned, then the Cache Node800 in the “bottom” position 880 is selected to be replaced. To do so,the cached data associated with the “bottom” Cache Node 880 can bewritten to a disk location specified in the DataGee field 810 of the“bottom” Cache Node 880, and the DataGee 810 from the “bottom” CacheNode 880 is returned to its location in the Gee Table 320. The “bottom”Cache Node 880 can then be overwritten by data for a new data block.

In one embodiment, the server nodes 150, 151 in the cluster 160 do nothave access to one another's cache memory. Therefore, unlike themetadata structures described in FIGS. 4-7, the Cache Node Table 350 isnot replicated across the servers 130, 131 of the cluster 160.

Lock Nodes and Refresh Nodes

In addition to the metadata structures described above in connectionwith FIGS. 3-8, other metadata structures can be used to enhance thesecurity and the efficiency of the file system 250. Two metadatastructures, a Lock Node Table and a Refresh Node Table, assist with themanagement of “shares” and “locks” placed on the files of the servernode 150. A share or a lock represents a client's request to limitaccess by other clients to a given file or a portion of a file.Depending on its settings, as will be described in greater detail below,a share or a lock prevents other client processes from obtaining orchanging the file, or some portion of the file, while the share or lockis in force. When a client requests a share or a lock, it can either begranted, or, if it conflicts with a previously granted share or lock, itcan be given a “pending” status until the original share or lock iscompleted.

Information about current shares and locks placed on a server node'sfiles is stored in a Lock Node Table. A Lock Node Table includes LockStrings, where each Lock String describes the current and pending sharesand locks for a given file.

FIG. 9 shows the structure of one embodiment of a Lock String 900. TheLock String 900 includes five nodes 911,912, 921, 922, and 923. Thefirst two nodes 911 and 912 are Share Nodes 910. The next three nodes921-923 are Lock Nodes 920. As shown in FIG. 9, in one embodiment, ShareNodes 910 precede Lock Nodes 920 in the Lock String 900.

The Share Nodes 910 have eight fields 930-937, and the Lock Nodes 920have ten fields 930-933 and 938-943. In FIG. 9, the first four fields ofboth the Share Nodes 910 and the Lock Nodes 920 are the same, and assuch, a description of one shall be understood to apply to both ShareNodes and Lock Nodes.

A lockStatus field 930 indicates whether the node is of type SHARE orLOCK, or if it is currently an unused FREE node. A SHARE node representsa current or pending share request. A share applies to an entire file,and, if granted, it specifies the read and write permissions for both arequesting client and for all other clients in the system. A LOCK noderepresents a current or pending lock request. A lock applies to aspecified byte range within a file, and, if granted, it guarantees thatno other client process will be able to access the same range to write,read or read/write, depending on the values in the other fields, whilethe lock is in effect.

A timeoutCt field 931 helps to ensure that locks and shares are notinadvertently left in effect past their intended time, due to error,failure of a requesting client process, or other reason. Locksautomatically “time out” after a given length of time unless they are“refreshed” periodically.

A next field 932 points to the next node in the Lock String 900. Apending field 933 indicates whether the lock or share represented by thenode is active or pending.

The fields 934-937 of FIG. 9 contain additional information useful tothe Share Nodes 910. An access field 935 indicates the kind of access tothe file that the client desires. In one embodiment, the access field935 may take on one of four possible values: 0 indicates that no accessto the file is required; 1 indicates that read only access is required;2 indicates that only write access is required; and 3 indicates thatread and write access to the file are both required.

A mode field 934 indicates the level of access to the file that anotherclient process will be permitted while the share is in effect. In oneembodiment, the mode field 934 can take on one of four possible values:0 indicates that all access by other client processes is permitted; 1indicates that access to read the file is denied to other clientprocesses; 2 indicates that access to write to the file is denied toother client processes; and 3 indicates that both read and write accessare denied to other client processes.

A clientID field 936 identifies the client that requested the share. Auid field 937 identifies the user on the client that has requested theshare or lock.

Fields 938-943 of FIG. 9 contain additional information useful to LockNodes 920. An offset field 938 indicates the starting point of the byterange within the file where the lock is in effect. A length field 939indicates the length of the segment (beginning at the offset point) thatis affected by the lock. In one embodiment, Lock Nodes 920 are keptordered within the Lock String 900 according to their offset field 938.

An exclusive field 940 indicates whether the lock is exclusive ornon-exclusive. An exclusive lock, sometimes called a write lock, is usedto guarantee that the requesting process is the only process with accessto that part of the file for either reading or writing. A non-exclusivelock, often called a read lock, is used to guarantee that no one elsemay write to the byte range while the requesting the process is usingit, although reading the file is permitted to other clients.

A clientID field 941 identifies the client that requested the lock. Auid field 942 identifies the user on the client that is requesting thelock. A svid field 943 identifies the process that is requesting thelock.

In one embodiment, a Refresh Node Table is used to detect clients whohold locks or shares on files and who are no longer in communicationwith the DFSS 100. A Refresh Node is created for each client thatregisters a lock or share. FIGS. 10 and 11 depict examples of howRefresh Nodes can be configured as a binary tree and as a doubly-linkedlist, respectively. Based on the task at hand and on the links used fortraversal, both structures can exist simultaneously for the same set ofRefresh Nodes, as will be explained in greater detail below.

Referring to FIG. 10, six Refresh Nodes 1000, 1010, 1020, 1030, 1040,and 1050 are shown configured as a binary tree. The structure of eachRefresh Node is the same, and it is to be understood that a detaileddescription of one Refresh Node 1000 applies also to the other RefreshNodes 1010, 1020, 1030, 1040 of FIG. 10. In one embodiment, the RefreshNode 1000 includes six fields. A clientID field 1001 identifies a clientwho has registered at least one current lock or share. A counter field1002 maintains a counter that, in one embodiment, is originally set to agiven start value and is periodically decremented until a “refresh”command comes from the client to request that the counter be returned toits full original value. If the counter field 1002 is allowed todecrement to a specified minimum value before a “refresh” command isreceived from the identified client 1001, then all locks and sharesassociated with the client 1001 are considered to have “timed out,” andthey are removed from their respective Lock Strings 900.

In one embodiment, Refresh Nodes are allocated from a flat array ofRefresh Nodes. The Refresh Nodes can be linked and accessed in a varietyof ways, depending on the task at hand, with the help of pointer fieldslocated in each node. For example, when a “refresh” command arrives fromthe client 110, it is advantageous to be able to quickly locate theRefresh Node 1000 with the associated clientID field 1001 in order toreset its counter field 1002. A binary tree structure, as shown in theexample of FIG. 10, can allow for efficient location of the Refresh Node1000 with the given clientID field 1001 value if the nodes of the treeare organized based on the clientID field 1001 values. In such a case, aleft link field 1003 (ltLink) and a right link field 1004 (rtLink),pointing to the Refresh Node's left and right child, respectively,provide links for traversal of the tree using conventional algorithmsfor traversing a binary tree.

In one embodiment, unused Refresh Nodes 1100, 1110, 1120, 1130 in theflat array are kept in a doubly-linked Free List, such as the onedepicted in FIG. 11, for ease of allocation and de-allocation. In oneembodiment, used Refresh Nodes are kept in a doubly-linked list, calleda Used List. With this structure, decrementing the counter field 1002 ofeach Refresh Node that is currently in use can be carried outefficiently. In FIG. 11, a stackNext field 1105 and a stackPrev field1106 of the Refresh Node 110 together allow for doubly-linked traversalof the Refresh Nodes of the Free List and the Used List. When a newRefresh Node is needed, it can be removed from the Free List and linkedto both the Used List and the binary tree by the appropriate setting ofthe link fields 1003, 1004, 1105, and 1106.

Intent Log

In one embodiment, the Filename Table 310, the G-node Table 330, the GeeTable 320 and the Gnid Table 340 are cached as well as being stored onthe disk array 140. In one embodiment, when the server 130 changes aportion of the metadata in cache, an entry is made into an Intent Log innon-volatile memory, such as flash memory or battery-backed RAM. TheIntent Log Entry documents the intention to update both the version ofthe metadata stored on the disk array 140 and any mirrored version(s) ofthe metadata on other server nodes 151 of the cluster 160. The IntentLog provides protection against inconsistencies resulting from a powerloss before or during an update.

The following is a list of steps that show the general use of the IntentLog:

-   -   1. Cached metadata is updated at the time of the original        change.    -   2. An intention to update the disk version of the metadata is        put into the Intent Log.    -   3. A copy of the intention is transmitted to other server nodes        of the cluster.    -   4. The intention to write metadata to disk on the first server        node is executed.    -   5. The intention to write metadata to disk on the other server        nodes is executed.    -   6. The Intent Log Entry on the first server is deleted.    -   7. Notice of the first server's Intent Log Entry is sent to the        other server nodes.

FIG. 12 shows the structure of an Intent Log Entry 1200. In oneembodiment, the Entry 1200 includes seven fields. A status field 1210designates whether the intention is FREE, WAITING, or ACTIVE. AnintentType field 1220 designates the type of metadata that is to beupdated. For example, the update may apply to a G-node, a Gnid, a Gee, aFilename Entry, or to a file's last access time (aTime). AgoalBufferIndex field 1230 points to an entry in a Goal Buffer that isused to verify the update. Field 1240 is a spare field that helps alignthe fields to a 64 bit boundary. A driveSector field 1250 and a drivefield 1260 identify the location on disk where the update is to be made.An intentData field 1270 holds the data of the update.

File Handle

A file handle is provided to clients by the DFSS 100 for use whenrequesting access to a file. Each file handle uniquely identifies onefile. The DFSS 100 treats both normal data files and directories asfiles, and provides file handles for both. In the description thatfollows, the term “file” may apply to either a data file or a directoryfile, unless specifically limited in the text.

FIG. 13 shows the structure of one embodiment of a file handle 1300 as a32-bit number with three fields. A Recommended NIC field 1310 indicateswhich of a server's Network Interface Connections (NICs) is recommendedfor accessing the file associated with the file handle 1300. FibreChannel typically provides two ports per server; accordingly, in oneembodiment, the Recommended NIC field 1310 is one bit in size.

A ServerID field 1320 identifies, by means of a server identificationnumber (ServerID), the primary owner of the associated file. Theinclusion of the file owner's ServerID 1320 in the file handle 1300enables a user on the client 110 to access a file in the distributedfile system 250 without needing to knowing explicitly which server nodeis holding the desired file. Using the file handle 1300 to request afile from the file system software 250 allows the file system software250 to direct the request to the appropriate server. By contrast,conventional UNIX file handles do not include information regarding theserver storing a file, and they are therefore not able to accommodatethe level of transparent file access provided in the file systemsoftware 250.

In one embodiment, clusters 160 include only two server nodes 150, 151,and the ServerID of the file's secondary owner can be obtained by“flipping” the least significant bit of the field 1320. This ability isuseful when the primary owner 150 is very busy and must issue a “retrylater” response to a client's request to read a file. In return, theclient 110 can temporarily change the ServerID in the file's file handle1300 and re-send the read request to the file's secondary owner 151.Similar accommodations can be made for clusters of more than two servernodes.

A G-node Index field 1330 provides an index into the file's G-node inthe G-node Table 330 on the server identified in the ServerID field1320.

In one embodiment, the file handle for a given file does not changeunless the file is moved to another server node or unless its G-nodelocation is changed. Thus, the file handle is relatively persistent overtime, and clients can advantageously store the file handles ofpreviously accessed files for use in subsequent accesses.

File Handle Look-Up

In order to access a desired file, the client 110 sends the file's filehandle 1300 and a request for file access to the file system 250. As wasillustrated in the embodiment shown in FIG. 13, the file handle 1300 ofa given file comprises information to identify the server that storesthe file and the location of the file's G-node 600 in the G-node Table330. With the information found in the G-node 600, as described in theexample of FIG. 6, the desired file can be located and accessed.

The file handle 1300 for a given file remains relatively static overtime, and, typically, the client 110 stores the file handles 1300 offiles that it has already accessed for use in subsequent accessrequests. If the client 110 does not have a desired file's file handle1300, the client 110 can request a file handle look-up from the filesystem 250 to determine the needed file handle 1300.

In one embodiment of a file handle look-up process, the DFSS 100 acceptsthe file handle 1300 of a parent directory along with the filename of adesired child file, and the DFSS 100 returns the file handle 1300 forthe desired child file. If the client 110 does not know the file handle1300 for the desired file's parent directory, then the client 110 canuse the file handle 1300 for any directory along the pathname of thedesired file and can request a file handle look-up for the nextcomponent on the desired pathname. The client 110 can then iterativelyrequest a file handle look-up for each next component of the pathname,until the desired file's file handle 1300 is returned.

For example, if the client 110 desires the file handle 1300 for a filewhose pathname is “root/WorkFiles/PatentApps/DesiredFile” and if theclient 110 has the file handle 1300 for the parent “Patent Apps”directory, then the client 110 can send the look-up request with the“PatentApps” file handle 1300 to get the “DesiredFile” file handle 1300.If the client initially has no file handle 1300 for the parent“PatentApps” directory, but does have the file handle 1300 for the“WorkFiles” directory, then the client 110 can send a first look-uprequest with the known “WorkFiles” file handle 1300 together with thefilename for the “PatentApps” directory. The DFSS 100 returns the filehandle for the “PatentApps” directory. Since the client 110 still doesnot have the needed “DesiredFile” file handle 1300, the client 110 cansend a second file handle look-up request, this time using the newlyreceived “PatentApps” file handle and the “DesiredFile” filename. Inresponse, the file system 250 returns the “DesiredFile” file handle1300. In this way, beginning with the file handle 1300 for any filealong the pathname of a desired file, the file handle 1300 for thedesired file can eventually be ascertained.

In one embodiment, when the client 110 first accesses the file system250, the client 110 is provided with one file handle 1300, namely thefile handle for a “root” directory. The “root” directory is thedirectory that contains all other directories, and is therefore thefirst component on the pathname of every file in the system. Thus, ifneed be, the client 110 can begin the look-up process for any file'sfile handle 1300 with a look-up request that comprises the “root” filehandle and the filename of the next component of the desired file'spathname. The final file handle returned will provide the client withthe information needed to accurately locate the desired file.

FIG. 14A shows an example of the file handle look-up procedure in whichthe client 110 has a file handle 1300 for a desired file's parentdirectory and needs a file handle for the desired file itself. Theclient 110 initiates a look-up for the desired file handle by sending alook-up request 1410 that comprises a filename 1420 of the desired fileand the file handle 1300 of the parent directory. The ServerID field1320 in the file handle 1300 identifies the server 130 of the node 150where the parent directory is stored, and the file system software 250directs the look-up request 1410 to the identified server 130. TheG-node index field 1330 stores an index for the parent directory'sG-node in the G-node Table 330 on the identified server.

In this example, the filename 1420 of the desired file is “AAAAA.” TheServerID field 1320 indicates that the parent directory is stored on theserver 130 with ServerID “123,” and the G-node index field 1330 showsthat a G-node for the parent directory can be found at index location“1” in the G-node Table 330.

When the server 130 receives the look-up request 1410, the server 130uses information in the G-node index field 1330 of the file handle 1300to access a G-node 1432 at index location “1.”

As described above, the G-node 600 acts as a repository of generalinformation regarding a file. In the example illustrated in FIG. 14A,the File Attribute-type field 602 of the G-node 1432, namely “NFDIR,”indicates that the file associated with the G-node 1432 is a directory,not a regular data file.

As described earlier, the Gnid-string 700 holds information about thechildren files of a given directory. The Child Gnid Index 628 in G-node1432 points to a first Gnid 1436 in the directory's Gnid-string 700. Theserver 130 searches for the desired data file amongst the children filesof the parent directory by searching the corresponding Gnids on thedirectory's Gnid-string. The server 130 uses the Filename Ptr fields 760of each Gnid 710 to access the associated file's filename entry 410 forcomparison with the filename 1420 of the desired file.

In FIG. 14A, the Child Gnid Index field 628 of G-node 1432 indicates avalue of “3,” and the server 130 accesses the Gnid 1436 at indexlocation “3” in the Gnid Table 340. To determine a filename associatedwith the Gnid 1436, the server 130 uses the Filename Ptr field 760 toaccess the Filename Entry 1438 associated with the Gnid 1436 at index“3.” To ascertain if the filename stored at the Filename Entry 1438matches the filename 1420 in the look-up request 1410, the server 130first compares the checksum and filename length count of the filename1420 in the look-up request 1410 with the checksum 412 and the filenamelength count 413 stored in the Filename Entry 1438 in the Filename Table310. (Note: These checksums and filename lengths are not shownexplicitly in FIGS. 14A and 14B.) If the aforementioned checksums andfilename length counts match, the server 130 proceeds with acharacter-by-character comparison of the character string 1420 in thelook-up request 1410 and the filename 414 in the Filename Entry 1438.

If a mismatch is encountered during the comparisons, as is the case inFIG. 14A, where the Filename Entry 1438 holds a filename of“ABCD” andlength “4” while the desired filename of “AAAAA” has a length of “5,”then the current Gnid is eliminated from consideration. Afterencountering a mismatch for the Gnid 1436 at index “3,” the server 130continues to traverse the Gnid-string 700 by using the Sibling Gnid Ptrfield 740 in the current Gnid 1436 as an index pointer.

The Sibling Gnid Ptr field 740 of the Gnid 1436 holds a value of “4,”indicating that a next Gnid 1440 can be found at index location “4” ofthe Gnid Table 340. When the checksum and name length for the desiredfilename 1420 do not match those from a Filename Entry 1442 “DE” foundat index location “0” of the Filename Table 310, the server 130 againeliminates the current Gnid from consideration.

The server 130 again uses the Sibling Gnid Ptr field 740 as a pointer,this time from the Gnid 1440 at index location “4” to a Gnid 1444 atindex location “6” in the Gnid Table 340. Following the Filename Ptr 760of the Gnid 1444 to Filename Entry 1446 and performing theaforementioned checksum, filename length, and filename comparisonsreveals that the desired filename 1420 and Filename Entry filename 1446do match. The server 130 therefore determines that this Gnid 1444 isassociated with the desired file.

In order to send the desired file handle 1300, which comprises theServerID 1320 and G-node Table index 1330 for the desired file, to therequesting client 110, the server 130 accesses the G-node Ptr field 750of the current Gnid 1444. The G-node 600 of a file is stored on theserver node 150 where the file is stored, which is not necessarily thesame server node that holds its parent directory. The G-node Ptr field750 provides both the ServerID of the server that is the file's primaryowner and an index that identifies the file's G-node 1448 in the primaryowner's G-node Table 330.

In the example of FIG. 14A, the contents of the G-node Ptr field 750show that the desired G-node 1448 exists at location “9” in the G-nodetable 330 on the same server 130, namely the server with ServerID “123.”However, it would also be possible for the G-node Ptr field 750 tocontain an index to a G-node Table 330 on another server 132, in whichcase, the file handle 1300 would include the ServerID of the server 132holding the file and its G-node 600. (This possibility is indicated bythe dotted arrow 1460 pointing from the G-node Ptr field 750 to anotherserver 132 of the DFSS 100.) Thus, the information in the G-node Ptrfield 750 allows the server 130 to provide the client 110 with both aServerID 1320 and with the G-node Index 1330 needed to create the filehandle 1300 for the desired file. The file handle 1300 for the desiredfile can be sent back to the client 110 for use in future access of thedesired file, and the process of file handle look-up is complete.

FIG. 14B shows one example of a file access operation, illustrated usingthe same context as was used in FIG. 14A. Here, the client 110 alreadyhas a file handle 1301 for the desired file, so an access request 1411can be sent directly to the file system 250. As previously disclosed,the user on the client 110 has no need to be aware of the specificserver node 150 that will be accessed. This information is embedded inthe desired file's file handle 1301.

The server 130, indicated in a ServerID field 1321, accesses the G-node1448 at index “9” as indicated in a G-node index field 1331 of the filehandle 1301.

As disclosed above, the Gee Table 320 holds information about thephysical storage locations of a file's data and parity blocks on thedisk array 140. The Gee Table 320 also holds information that helpslocate blocks of data that have been copied to cache. A Gee holdsstorage location information about one block of data. Gees for a givenfile are linked together to form the gee-string 500. A first Gee of thegee-string 500 is called the root of the gee-string 500.

The Gee Index-Root field 636 of the G-node 1448 provides an index to aroot Gee 1450 in the Gee Table 320. Reading the data field 591 of theGee 1450 confirms that this Gee is a root Gee and that it is associatedwith the G-node 1448 at index location “9.” The server 130 continuesreading the gee-string at the next contiguous Gee 1452 in the Gee Table320. Reading the G-code 590 of the Gee 1452 with its value of “CACHEDATA” reveals that this Gee represents data that has been cached.

As disclosed above, the Cache Node Table 350 holds information thatallows the server 130 to access a file block's location in cache 1456.Reading the Data Field 591 of a next Gee 1452 provides a pointer to anappropriate cache node 1454 of the Cache Node Table 350. The cache node1454 holds the CacheBlockAddr field 825 which points to a location 1458in cache 1456 of the data associated with the Gee 1452. The cache node1454 also holds a copy of the associated Gee 1452 from the Gee Table 320in the Data Gee field 810 until the associated data block 1458 is nolonger stored in cache. The Data Gee field 810 also provides a pointerto the location of the associated file data stored on the server node'sdisk array 140. By following the pointers from the file handle 1301 tothe G-node 1448 at index location “9”, on to the Gees 1450 and 1452 atindex locations “2” and “3,” on to the Cache Node 1454 at index location“7,” and finally on to cache location “w” 1458, the data originallyrequested by the client 110 can be accessed for reading, writing, orother operations, and the process of file access is complete.

FIGS. 15-17 present a set of interrelated flow charts that illustratethe process of file access, including file handle look-up, if necessary.

Referring to FIG. 15, a process 1500 of accessing a file is described,beginning with the request for a file handle look-up, through the use ofthe file system's metadata structures, to final access of the file datain cache.

Beginning at a start state 1505, the process 1500 moves to a state 1510where the client 110 determines whether it has the file handle 1300 fora file that it wishes to access.

If the client 110 does not have the desired file handle 1300, theprocess 1500 moves to a state 1515, where the client 110 and one or moreservers of the DFSS 100 perform a file handle look-up, as will bedescribed in greater detail with reference to FIG. 16.

Returning to the state 1510, if the client 110 determines that it doeshave the desired file handle 1300, then the process 1500 moves on to astate 1520 where the client 110 sends the file access request 1411 tothe server 130 indicated in the file handle 1300.

From state 1520, the process 1500 moves to a state 1525 where the server130 accesses a G-node 600 indicated in the file handle 1300.

Moving on to a state 1530, the server 130 uses a pointer in the G-node600 to access an appropriate Gee in the Gee Table 320. Severalpossibilities exist for appropriate gees, depending on the currentaccess needs of the server 130. For example, in the embodiment of theG-node 600 described in FIG. 6, seven fields 630-636 relate to pointersto the Gee Table 320. The Gee Index-Root field 636 is an index to theroot Gee, which can be used, for example, when reading from thebeginning of a file is desired. Fields 634 and 635 together point to thelast Gee of a file, which can be used, for example, when appending newdata to the end of a file. Fields 630 and 631 together point to a mostrecently used Gee for the file, which can be used, for example, forsequential access to the gees of a file. Fields 632 and 633 togetherpoint to a middle Gee for the gee-string 500 which can be used, forexample, when access to the middle, or second half, of the file isdesired.

After accessing an appropriate Gee in the state 1530, the process 1500moves on to a state 1535 where the server 130 reads the G-code field 590in order to determine if the data represented by the Gee has alreadybeen cached. If the G-code 590 holds a value other than “CACHE DATA” or“CACHE PARITY,” the server 130 assumes that the desired data has not yetbeen cached, and the process 1500 moves to a state 1540 where thedesired data is sent to cache. The state 1540 is described in greaterdetail in connection with FIG. 17 below.

Returning to the state 1535, if the server 130 determines that theG-code 590 holds a value of “CACHE DATA” or “CACHE PARITY,” the server130 assumes that the desired data has already been cached. The process1500 then moves on to a state 1545 where the server 130 accesses thecache node 800 indicated in the gee's data field 591.

From the state 1545, the process 1500 moves on to a state 1550 where theserver 130 manipulates the accessed cache node 800 as needed accordingto the description of FIG. 8B. For example, if the cache node 800 iscurrently on the Normal List 860, and the client 110 has requested toread the data block, the server 130 can increment the cache node'sReadCt field 830 and move it to the Read List 870.

Once the Cache Node 800 is properly updated, the process 1500 moves fromthe state 1550 to a state 1555 where the server 130 accesses the fileblock data in the cache location indicated in the Cache Node 800. Fromhere, the process 1500 moves on to a state 1560 where the server 130performs a desired operation on the cached data block. From the state1560, the process 1500 moves on to a state 1570 where accessing the fileis complete.

In FIG. 15, the process 1500 reaches the state 1515 only if the client110 does not have a file handle 1300 for the desired file. Referring tothe embodiment of the file handle 1300 illustrated in FIG. 13, the filehandle 1300 for a given file comprises, among other possible fields, aServerID field 1320 identifying the server 130 that stores the data andmetadata for a file, as well as a G-node Index field 1330 that indicatesthe G-node 600 of the given file on that identified server 130.

FIG. 16 is a flow chart that describes in more detail how the process ofthe state 1515 carries out a file handle look-up. The look-up process1515 begins with a look-up request that comprises the file handle 1300for a directory on the pathname of the desired file and continues onthrough each component of the pathname, retrieving a file handle foreach, until a file handle for the desired file itself is returned to theclient 110.

The “root” directory is the first component of the pathname for everyfile in the file system, and, if necessary, the client 110 can begin theprocess of file handle look-up 1515 with the file handle of the “root”directory. In one embodiment, every client has at least the file handle1300 for a “root” directory for the file system 250. For example, the“root” directory can be known to reside on the server 130 with ServerIDnumber 0, and its G-node 600 can be known to reside at index 0 of theG-node Table 330 on Server 0. However, it may also be that at thebeginning of the look-up process 1515, the client 110 has the filehandle 1300 for the desired file's parent directory or for anotherdirectory on the pathname of the file, and that by beginning with one ofthese directories “closer” to the file itself, the look-up process maybe shortened.

Beginning at a start state 1605, the process 1515 moves to a state 1610where the client 110 sends the look-up request 1410 comprising the filehandle 1300 for a directory and the filename 1420 of a desired nextcomponent. The look-up request 1410 is sent to a server 1300 indicatedin the file handle 1300 field of the look-up request 1410. The process1515 next moves to a state 1615, where the server 130 accesses a G-node600 indicated in the file handle 1300 of the look-up request 1410.

Moving on to a state 1620, the server 130 uses the ChildGnidIndex field628 in the G-node 600 to access a first Gnid 710 in the directory'sGnid-string 700. As described in connection with the embodiment shown inFIG. 7, the Gnid-string 700 is a linked list of Gnids 710, with one Gnid710 for each child file in a parent directory.

Moving on to a state 1625, the server 130 calculates a checksum andfilename length for the filename 1420 of the next desired pathnamecomponent that was sent by the client 110 in the look-up request 1410.Having a checksum and filename length for a desired file allows theserver 130 to expedite searching for a matching Filename Entry becausecomparison of checksums and comparison of filename lengths can beaccomplished much more quickly than a character-by-character comparisonof the filenames themselves. Performing the first two types ofcomparisons before embarking on the character-by-character comparisonallows the server 130 to eliminate any Filename Entries whose checksumand filename length do not match, before performing the more costlycharacter-by-character filename comparison.

Moving on to a state 1630, the server 130 uses the FilenamePtr field 760of the currently accessed Gnid 710 to locate the associated FilenameEntry 410 in the Filename Table 310. Moving on to a state 1635, theserver 130 determines if the checksum 412 stored in the currentlyaccessed Filename Entry 410 is greater than the checksum calculated inthe state 1625.

As described in connection with FIG. 7, in one embodiment, Gnids 710 arestored in the Gnid-string 700 in order of checksum 412 values calculatedfor their associated character strings 414, with the Gnid 710 having thesmallest checksum 412 value coming first. This ordering of Gnids 710 bychecksum 412 value allows the server 130 to determine whether a desiredfilename may still exist on the given Gnid-string 700. In thisembodiment, if, in the state 1635, the server 130 determines that thechecksum 412 found in the currently accessed Filename Entry 410 isgreater than the checksum calculated in the state 1625, then a Gnid 710for the desired file (with the lower checksum) cannot exist on thecurrently accessed Gnid-string 700. In this case, the process 1515 moveson to a state 1640, where it reports a File-Not-Found Error to theclient 110.

Returning to the state 1635, if the server 130 determines that achecksum found in a currently accessed Filename Entry is greater thanthe checksum calculated in state 1625, then the process 1515 moves on toa state 1645.

In the state 1645, the server 130 determines if the checksums and thefilename lengths from the two sources match. If either the checksums orthe filename lengths (or both) do not match, then this Filename Entrycan be ascertained not to be associated with the client's desired file,and the process 1515 moves on to a state 1660. In the state 1660, theserver 130 uses the SiblingGnidPtr 740 in the current Gnid 710 to accessthe next Gnid in the current Gnid-string.

Returning to the state 1645, if the server 130 determines that thechecksums and filename lengths do match, then this Filename Entry 410cannot yet be eliminated, and the process 1645 moves on to a state 1650,where the server 130 performs a character-by-character comparison of thetwo filenames.

If, in the state 1650, the server 130 determines that the two filenamesdo not match, then, as was the case in state 1645, this Filename Entrycan be ascertained not to be associated with the client's desired file.In this case, the process 1515 moves on to a state 1660, where theserver 130 uses a SiblingGnidPtr 740 in the current Gnid to access anext Gnid 711 in the current Gnid-string 700.

From the state 1660, the process 1515 returns to the state 1630, and theserver 130 uses the Filename Ptr field 760 of the newly accessed Gnid711 to access an associated Filename Entry in the File Table 310. Thisloop through the states 1630, 1635, 1645, 1660 (and possibly 1650)continues until a Filename Entry and associated Gnid for the desiredfile is found or until an error is encountered.

If, in the state 1650, the server 130 determines that the filenames domatch, then the process 1515 has identified a Filename Entry and anassociated Gnid that corresponds to the desired file. In this case, theprocess 1515 moves on to a state 1655, where the server 130 sends thedesired file handle 1300 information back to the client 110. Moving onto a state 1665, the file handle look-up process 1515 is complete. Theprocess 1500 from FIG. 15 then proceeds from the state 1515 back to thestate 1510 and continues as described in the explanation of FIG. 15.

FIG. 17 presents a more detailed description of the state 1540 from FIG.15, in which uncached data that has been requested for access by theclient 110 is copied into cache memory. The process 1540 of caching filedata begins in a start state 1705 and proceeds from there to a state1110, where the server 130 identifies the least recently used cache node880. In one embodiment of the file system 250, when the three-listscheme described in FIG. 8B is used, the server 130 can easily identifythe least recently used cache node 880 because it is a “last” cache nodeon the Normal List 860 of the scheme.

Moving on to a state 1720, the server 130 writes the associated filedata from its volatile location in cache to its non-volatile location ondisk array 140, which is indicated in the DataGee field 810 of the cachenode 800.

Moving on to a state 1730, the server 130 copies the DataGee field 810from the cache node 800 back to its original position in the Gee Table320, changing the G-code 590 back from “CACHE DATA” to “DATA” or from“CACHE PARITY” to “PARITY,” indicating that the associated data is nolonger cached.

Moving on to a state 1740, the server 130 overwrites the DataGee field810 in the cache node 800 with a Gee from the Gee Table 320 that isassociated with a new file block to be cached.

Moving on to a state 1750, the server 130 caches the new file block fromdisk to a cache location associated with the cache node.

Moving on to a state 1760, the process 1540 of caching file data iscomplete, and the process 1500 in FIG. 15 can proceed from the state1540 on to the state 1545 to continue the task of accessing a file.

Referring to FIG. 18, a process of file allocation 1800 is shown inflowchart form. The process 1800 begins in a start state 1805 and movesto a state 1810 where the client 110 send a file allocation request thatincludes a filename for a new file and a file handle for the new file'sparent directory.

The process 1800 moves to the state 1815, and the server node 150indicated in the parent directory's file handle receives the fileallocation request. For the purposes of the description of this figure,this server node 150 will be known as the “parent” server.

The process 1800 moves to the state 1820, and the “parent” server 150uses workload statistics received from the other server nodes of theDFSS 100 to decide if the file will be “owned” by the “parent” servernode 150 or by another server node.

If the “parent” server node 150 decides that it will be the owner of thenew file, then the process 1800 moves to a state 1830, where the“parent” server creates a new file, makes an appropriate new FilenameEntry 410 in the Filename Table 310, and allocates a new G-node 600 forthe new file. At this point, the “parent” server node 150 has enoughinformation to create the file handle 1300 for the new file.

Returning to the state 1820, if the “parent” server node 150 decidesthat another server node should own the new file, the process 1800 movesto a state 1850, where the “parent” server 150 sends a file allocationrequest to another server of the DFSS 100. For the purposes ofdescribing this figure, the other server will be known as the “second”server.

From the state 1850, the process 1800 moves to a state 1855 where the“second” server creates a new file, makes the appropriate new FilenameEntry 410 in the Filename Table 310, and allocates the new G-node 600for the new file. At this point, the “second” server has enoughinformation to create the file handle 1300 for the new file.

From the state 1855, the process 1800 moves on to a state 1860, wherethe “second” server sends the file handle 1300 for the new file to the“parent” server node 150.

At this point, when the “parent” server node 150 has the file handle1300 for the new file, the process 1800 moves on to a state 1835.

The state 1835 can also be reached from state 1830 in the case where the“parent” server 150 decided to be the owner of the file. As disclosedabove, in state 1830 the “parent” server 150 also had the information tocreate a file handle 1300 for the new file, and the process 1800 alsomoves on to a state 1835.

For either case, in state 1835, the “parent” server node 150, as ownerof the new file's parent directory, allocates a Gnid 710 for the newfile, adds it to the appropriate Gnid-string 700, and, if one does notalready exist, the “parent” server node 150 makes an appropriate newFilename Entry 410 in the Filename Table 310.

From state 1835, the process 1800 moves on to a state 1840, where the“parent” server node 150 sends the file handle 1300 for the new file tothe requesting client 110.

The process 1800 moves on to a state 1845 where the process of fileallocation is now complete. The requesting client 110 can access the newfile using the newly received file handle 1300, and since the filehandle 1300 contains identification for the server that owns the newfile, any access request can be automatically routed to the appropriateserver node.

Redirectors

In various embodiments, the DFSS 100 can be configured to store andmanage a very large number of files of widely varying sizes. In someembodiments, it can be advantageous to store all of the file metadata ondisk, while copies of the metadata for only some of the most recentlyused files are additionally cached in volatile memory. In someembodiments, memory for metadata structures can be dynamically allocatedas new metadata structures are brought from disk to volatile memory.

FIG. 19 depicts one embodiment of a scheme to allow for efficient accessto file metadata when not all metadata is kept in volatile memory. Inthe embodiment shown in FIG. 19, a G-node Redirector (GNR) array 1900 involatile memory holds a G-node Redirector (GNR) 1910 per file. TheG-node Redirector (GNR) is a small data structure that comprisesinformation for locating the G-node 600 of a desired file, includinginformation regarding whether the file's G-node 600 is currently incache 1920. In the embodiment shown in FIG. 19, a client 110 requestingaccess to a given file sends a file handle 1300 that includes an indexfor the desired G-node Redirector (GNR) 1910 in the G-node Redirector(GNR) array 1900, which references the G-node 600 of the desired file.In one embodiment, when a desired G-node 600 is not currently cached, aleast recently used G-node 600 in cache 1920 can be removed from cache1920, and a copy of the desired G-node 600 can be brought from the diskarray to the cache 1920.

Super G-nodes

In one embodiment, the file system 250 can be advantageously configuredto store file metadata in a data structure called a Super G-node (SG)that comprises the file's G-node, other file information, andinformation that allows the file system 250 to locate the physicalstorage locations of the file's data blocks, as will be described ingreater detail below.

FIG. 20A shows one embodiment of a Super G-node 2000 structure of fixedsize that can provide location information for files of a wide varietyof sizes. As shown in FIG. 20A, a Status field 2010 in the Super G-node2000 can be used to indicate a type of Super G-node that corresponds toa category of associated file sizes, as will be described in greaterdetail with reference to FIG. 20B. A Linking Information field 2020 canbe used to interconnect Super G-nodes 2000 into one or more linked listsor other structures. A G-node field 2030 comprises attribute and otherinformation about a corresponding file that is similar to theinformation stored in the G-node 600 embodiment described with referenceto FIG. 6. A File Location Data field 2040 in the Super G-node 2000allows the file system 250 to locate a file's data, as will be describedin greater detail below.

In the embodiment shown in FIG. 20A, the Super G-node 2000 comprises 16Kbytes of memory. The Status 2010, Linking Information 2020, and G-node2030 fields together comprise 128 Bytes of the Super G-node 2000, andthe remainder of the Super G-node can be used to store the File LocationData 2040.

FIG. 20B depicts one embodiment of a scheme that uses Super G-nodes 2000of a fixed size to hold information about files of widely differingsizes. In the embodiment shown in FIG. 20A, four types 2001-2004 ofSuper G-node 2000 are depicted.

A Super G-node 2000 of type Super G-node Data (SGD) 2001 can be used fora file that is small enough that its data 2005 can fit entirely withinthe File Location Data 2040 field of the SGD 2001. For the embodimentdescribed with reference to FIG. 20A, a small file refers to a file thatis 16,256 Bytes, or smaller. When a file's Super G-node 2000 is of typeSGD 2001, locating the file's data simply means reading it from the FileLocation Data 2040 field of the SGD 2001.

In the embodiment shown in FIG. 20B, a Super G-node 2000 of type SuperG-node Gee (SGG) 2002 can be used for medium files, that is, files ofsizes up to approximately 700 MegaBytes of data that are too large tofit into an SGD 2001. In an SGG 2002, the File Location Data 2040 fieldis used to hold a Gee String Packet (GSP) 2007 that comprisesinformation very similar to that of the Gee-String 500 described withreference to FIG. 5. As with the Gee-String 500, the Gee String Packet2007 comprises Gees 2006 that point to the physical locations of thefile's data 2005.

A Super G-node 2000 of type Super G-node List (SGL) 2003 can be used forlarge files whose Gee-String 500 is too large to be described by a GeeString Packet 2007 that fits within the SGL's 2003 File Location Data2040 field. Instead, the SGL's 2003 File Location Data 2040 field isused to hold a Gee String Packet Block (GSPB) 2008, which is a list ofpointers to a plurality of Gee String Packets 2007 that togetherdescribe the Gees 2006 that point to the locations of the file's data2005. In one embodiment, an SGL 2003 can reference files of sizes up toapproximately 490 GigaBytes.

A Super G-node 2000 of type Super G-node List of Lists (SGLL) 2004 canbe used for very large files. Here, the File Location Data 2040 field ofthe SGLL 2004 comprises a Gee String Packet List Block 2009 thatcomprises pointers to a plurality of Gee String Packet Blocks 2008 thatpoint to a plurality of Gee String Packets 2007 that points to aplurality of Gees 2006 that point to a plurality of storage locationsthat hold the desired data 2005.

In one embodiment, Gee String Packet List Blocks 2009, Gee String PacketBlocks 2008, and Gee String Packets 2007 are implemented in structuresthat are equivalent in size and organization to the Super G-node 2000described with reference to FIG. 20A, except that the G-node field 2030is not used.

Parity Groups

The foregoing description of a distributed file storage system addressesthe need for a fault tolerant storage system with improved reliabilityand scalability characteristics. This system features a flexible diskarray architecture that accommodates the integration of variably sizeddisk drives into the disk array and provides mechanisms to permit eachdrive's capacity to be more fully utilized than prior art systems. Inone embodiment, variably sized data and parity blocks are distributedacross the available space of the disk array. Furthermore, the systemprovides methods of redistributing data across the disk array to improvedata storage and retrieval, as well as, provide for improvedfault-tolerance. Another benefit of the data redistributioncharacteristics of the system is that it continues to providefault-tolerant data access in situations where many drives of the diskarray have failed. This feature is a notable improvement overconventional RAID systems that typically only provide fault-tolerancefor single (or at most two) drive failures.

FIG. 22A shows a file storage system 100 having the server node 150 thatoperates within a computer network architecture to provide data and filestorage. The computer network comprises one or more clients 110 thatexchange information with the server node 150 through the communicationsmedium or fabric 120 to store and retrieve desired data from the servernode 150. In one aspect, the clients 110 include one or more computingdevices that exchange information with the server node 150 through thecommunications medium 120.

The communications medium 120 can be any of a number of differentnetworking architectures including, for example, Local Area Networks(LAN), Wide Area Networks (WAN), and wireless networks which may operateusing Ethernet, Fibre Channel, Asynchronous Transfer Mode (ATM), andToken Ring, etc. Furthermore, any of a number of different protocols canbe used within the communications medium 120 to provide networkingconnectivity and information exchange capabilities between the clients110 and the server node 150, including, for example, TCP/IP protocols,Bluetooth protocols, wireless local area networking protocols (WLAN), orother suitable communications protocols.

The server node 150 includes the server 130 that serves as a front endto the disk array 140. The server 130 receives information and requestsfrom the clients 110 and processes these requests to store and retrieveinformation from the disk array 140. In one aspect, the server 130maintains at least a portion of an instruction set or file system thatdetermines how data and information are stored and retrieved from thedisk array 140.

Although the server node 150 is illustrated as a single entity in FIG.22A, it will be appreciated that many server nodes 150 can be connectedto the communications medium 120. Thus, a plurality of server nodes 150can be connected to the communications medium 120 and accessible to theclients 110 for the purposes of information storage and retrieval.Furthermore, the server nodes 150 can operate independently of oneanother or be configured to transparently present a single disk image toeach client 110 thus creating a unified storage area that facilitatesend user interaction with the server nodes 150. In one aspect, theserver nodes 150 incorporate functionality for maintaining the singledisk image through the use of the file system present in each of theservers 130 which provides communication and organization to create thesingle disk image.

FIG. 22B illustrates another embodiment of a file storage systemcomprising a distributed file storage system architecture. In thisembodiment, two or more server nodes 150, 151 are physically orlogically interconnected to form the cluster 160. File data stored onany server node is accessible to any other server in the cluster 160.The cluster 160 may also provide metadata and transaction mirroring.Furthermore, stored files may be replicated across at least two servernodes 150, 151 within the distributed file storage system 100 to provideincreased redundancy or data mirroring capabilities.

One advantage achieved by the aforementioned distributed configurationsis that they may provide increased data protection and/or faulttolerance. For example, if the replicated server node 150 fails orbecomes unavailable, the second replicated server node 151 can handleclient requests without service interruption. Another advantage achievedby using this interconnected arrangement is that alternative server nodeaccess paths 165 can be created where identical data can be readsimultaneously from the two or more interconnected server nodes 150,151. Thus, if one server node 150 in the cluster is busy andunavailable, another redundant server node 151 can service clientrequests to increase data throughput and accessibility. As with thesingle server node configuration, a plurality of clusters 160 may bepresent and accessible to the clients 110. Similarly, the clusters 160can be configured to present a single disk image to the clients 110 tofacilitate interaction by the end users of the distributed file storagesystem 100.

As shown in FIG. 22B, each disk array 140, 141 in the server nodes 150,151 can include a variable number of disks where each server node 150,151 has a different disk array configuration. Each disk within the diskarray 140, 141 can have a different storage capacity. These features ofthe distributed file storage system 100 contribute to improvedflexibility and scalability in configuring the server nodes 150, 151.

The variable disk configuration of the distributed file storage system100 overcomes a limitation present in many conventional storage systemswhich require that upgrades to the storage system be performed in acoordinated manner where all disks in each disk array 140, 141 arereplaced in unison. Additionally, many conventional storage systems,including RAID architectures, require strict conformity amongst the diskarrays within the system, as well as, conformity in disk capacity withinindividual disk arrays. The distributed file storage system 100 of thepresent invention is not limited by the restriction of uniform diskupgrades or conformity in disk capacity and can accommodate replacementor upgrades of one or more drives within each server node with drives ofdiffering capacity. To maintain data integrity and knowledge ofavailable storage space within the distributed file storage system 100,one of the functions of the aforementioned file system present in theservers 130, 131 is to accommodate differences in disk array capacityand disk number between the server nodes.

FIG. 23 illustrates the use of a distributed file storage mechanismwithin the disk array 140 to improve space utilization and flexibilityof data placement. A space mapping configuration 2300 is illustrated forthe disk array 140 where each disk 2305 is subdivided into a pluralityof logical blocks or clusters 2310. For the purposes of thisillustration the cluster size is shown to be fixed across all disks 2305of the array 140, although, as will be illustrated in greater detail insubsequent figures, the cluster size can be variable within each disk2305 and across disks 2305 within the array 140.

A first file 2320 having data to be stored on the disk array 140 issubdivided into one or more data blocks. The determination of the datablock size, number, and distribution is calculated by the file system asdata storage requests are received from the clients 110. Each data block2330 is mapped or assigned to a location within the disk array 140 thatcorresponds to the particular disk 2305 and logical block 2310 withinthe disk 2305. Unlike conventional disk arrays, the block size used fordata storage is variable from one block to the next within the file.

The server 130 organizes and distributes information to the disk array140 by dividing a file into one or more data blocks 2330 that aredistributed between one or more parity groups 2335. Each parity group2335 includes a discrete number of data blocks 2330 and further includesa parity block 2337 containing parity information calculated for thedata blocks 2330 contained within the particular parity group 2335.Unlike conventional systems, the size of the data blocks 2330 and parityblocks 2337 is not singularly fixed throughout the disk array 140. Thecollection of data blocks 2330 and parity blocks 2337 can include anumber of different sizes and configurations resulting in more flexiblestorage of data within the disk array 140.

Using File #1 in FIG. 23 as an example, the information contained in thefile is distributed in 7 data blocks corresponding to DATA₁ 1-DATA₁ 7.Each data block, DATA₁ 1-DATA₁ 7 is distributed between 3 parity groupswherein the first parity group contains DATA₁ 1-DATA₁ 2 the secondparity group contains DATA₁ 3-DATA₁ 4 and the third parity groupcontains DATA₁ 5-DATA₁ 7. Furthermore, 3 parity blocks PARITY₁ 1-2,PARITY₁ 3-4, and PARITY₁ 5-7 are formed, one for each parity group.

The parity groups 2335 are determined by the server 130 which assessesthe incoming data to be stored in the disk array 140 and determines howthe data is distributed into discrete data blocks 2330 and furthermorehow the data blocks 2330 are distributed into parity groups 2335. Afterdetermining the data block and parity group distribution, the server 140calculates the parity information for the data blocks 2330 in eachparity group 2335 and associates the parity block 2337 containing thisinformation with the appropriate parity group 2335.

The server 130 then determines how the information for each parity group2335 is stored within the disk array 140. Each data block 2330 andparity block 2337 is distributed within the disk array 140 in anarrangement where no blocks 2330, 2337 originating from the same paritygroup 2335 are stored on the same disk of the disk array 140. Thenon-overlapping storage of data blocks 2330 and parity blocks 2337derived from the same parity group 2335 creates the fault-tolerant datastorage arrangement where any block 2330, 2337 within a parity group2335 can be reconstructed using the information contained in the otherremaining blocks of the parity group 2335. This arrangement where blocks2330, 2337 associated with the same parity group 2335 are not be storedon the same disk 140 is important in case of a disk failure within thearray 140 to insure that that lost data can be reconstructed. Otherwise,if two or more blocks associated with the same parity group 2335 arestored on the same drive, then in the event of a disk failure, datarecovery can not be assured.

An example distribution of data blocks 2330 and parity blocks 2337within the disk array 140 is shown in FIG. 23. The 7 data blocks and 3parity blocks corresponding to the File #1 are distributed along disknumbers 0, 1, 8, 3, 7, 2 and 2110 respectively. In a similar manner, asecond file 2340 is divided into 4 data blocks (and 2 parity groups)that are distributed along disk numbers 0, 2, 4, and 5 respectively. Thesize, order, and placement of the data blocks is pre-determined by theserver 130 which assigns regions of each disk 2305, corresponding toparticular logical blocks, to store data blocks of designated sizes. Theparity blocks 2337 of the parity groups 2335 associated with the firstfile 2320 are further stored on disks 9, 6, 11 with the parity blocks2337 of the second file 2340 stored on disks 3, 9.

The data blocks 2330 and the parity blocks 2337 need not be sequentiallystored but rather can be distributed throughout the disk array 140.Using this arrangement, the distributed file storage system 100 permitsthe non-sequential assignment and storage of parity group information ina flexible manner that is not limited by a rigid order or placementschema. Flexible block placement in the aforementioned manner improvesdisk utilization within the disk array 140 and provides foraccommodating variable disk capacities as will be shown in greaterdetail in subsequent figures.

FIG. 24A illustrates a process 2400 for the storage of data and parityinformation within the distributed file storage system 100. The process2400 commences with a data storage request 2410 issued by the client 110to the server node 150. During this time the client 110 sends ortransmits data 2415 to the server node 150 which receives and preparesthe data 2420 for subsequent processing and storage. In one embodiment,the server node 150 includes hardware and/or software functionality toperform operations such as error checking, data buffering, andre-transmission requests, as needed, to insure that the data 2415 isreceived by the server 130 in an uncorrupted manner. Furthermore, theserver node 150 is able to process simultaneous requests from aplurality of clients 110 to improve performance and alleviate bandwidthlimitations in storage and retrieval operations. In one aspect, the data2415 is transmitted through the communications fabric 120 in the form ofa plurality of data packets that are automatically processed by theserver node 150 to generate the data 2415 that is to be desirably storedwithin the disk array 140.

Upon receiving the data 2420, the server 130 analyzes thecharacteristics of the data 2430 to determine how the data 2415 will bedistributed into one or more data blocks 2330. In one aspect, the dataanalysis 2430 includes identifying the content or type of data that hasbeen sent, such as, for example, multimedia data, textual data, or otherdata types. Using one or more of the plurality of available disk blockssizes, the server 130 identifies desirable block sizes and distributionmappings that are used to group the data 2415 and organize it into thedata blocks 2330.

The data 2415 is then parsed into blocks 2440 according to the dataanalysis 2430 and the resulting blocks are further arranged into one ormore parity groups 2450. The parity group arrangement determination 2450distributes the data blocks 2330 between the parity groups 2335 anddictates the size of the parity blocks 2337 that will be associated witheach parity group 2335. For example, a parity group composed of 3 datablocks having sizes of 128K, 64K, and 256K respectively will have adifferent associated parity block size than and parity group composed of2 data blocks having sizes of 128K and 256K. The server 130 cantherefore vary the block size as well as the parity group size in anumber of different ways to achieve improved storage and distributioncharacteristics within the disk array 140.

In one aspect, the distributed file storage system 100 is an improvementover conventional systems by allowing both data and parity blocks to beassigned to physical disk blocks. Furthermore, the mapping of the dataand parity blocks to the physical disk(s) may be performed either beforeor after the parity calculations thus improving storage flexibility.

Upon determining the parity group arrangement 2450, the server 130calculates the parity blocks 2460 for each parity group 2335. Aspreviously described, the parity block calculation 2450 creates afault-tolerant information block which is associated with each group ofdata blocks 2330 within the parity group 2335. The parity block iscalculated 2460 by selecting all data blocks 2330 in a parity group 2335and performing a logical operation on the data 2415 contained therein tocompute error correction information. In one embodiment, theerror-correction information is determined using the logical operation,exclusive OR to generate the parity information. Using thiserror-correcting information the parity block 2337 can be used torestore the information contained in a particular data block 2330 orparity group 2335 that may become corrupted. Furthermore, the parityinformation can be used to restore the contents of entire disks 2305within the disk array using the error correction information inconjunction with other non-corrupted data.

When the parity groups 2335 have been formed, the server 130 thendetermines how the data blocks 2330 and parity block 2337 for eachparity group 2335 will be distributed 2470 in the disk array. Although,the data 2415 can be striped sequentially across the disks 2305 of thedisk array 140, it is typically more efficient to map and distribute theblocks 2335, 2337 throughout the disk array 140 in a non-sequentialmanner (See FIG. 23). Mapping the data blocks 2330 in this mannerrequires knowledge of how the data blocks 2330 are positioned andordered within the disk array 140. Detailed knowledge of the mapping foreach data block 2330 is maintained by the server 130 using a filestorage mapping structure. This structure will be discussed below inconnection with FIGS. 7 and 9. Using the mapping schema determined bythe server 130, the blocks 2330, 2337 of each parity group 2335 arestored 2480 in the disk array 140.

As previously indicated, the distributed file storage system 100 employsa variable parity approach where the size of the parity block 2337 isnot necessarily constant. The server 130 creates parity blocks 2337 byselecting one of more data blocks 2330 for which error correctioninformation will be computed. The size of the parity block 2337 isdependent upon the number of data blocks 2330 whose error correctioninformation is computed and is determined by the server 130. In oneaspect, the server 130 selects a parity block size that is convenientand efficient to store within the existing space of the disk array 140.The server 130 also provides for distributed placement of the parityblocks 2337 in a manner similar to that of the data blocks 2330. Thus,both data blocks 2330 and parity blocks 2337 are desirably mappedthroughout the disk array 140 with the server 130 maintaining a recordof the mapping.

The server 130 insures that both data blocks 2330 and parity blocks 2337are appropriately positioned within the disk array 140 to insure somelevel of fault tolerance. Therefore, the server 130 desirablydistributes selected data blocks and parity blocks containing errorcorrection information for the selected data blocks on non-overlappingdisks (e.g. all blocks of a parity group are on separate disks). Thisinsures that if a disk failure does occur, that the corruptedinformation can be recovered using the remaining data/parity informationfor each parity group. Upon calculating the appropriate parityinformation and distribution mapping 2470, the parity blocks 2337 arestored in the disk array 2480 in a manner designated by the server 130.

FIG. 24B illustrates another embodiment of a process 2405 for thestorage of data and parity information within the distributed filestorage system 100. As with the aforementioned data and parityinformation storage method 2400, the process begins with the datastorage request 2410 issued by the client 110 to the server node 150.Subsequently, an analysis of the characteristics of the data 2430 isperformed to determine how the data 2415 will be distributed into theone or more data blocks 2330. The data 2415 is then parsed into blocks2440 according to the data analysis 2430 and the resulting blocks arefurther arranged into one or more parity groups 2450. The server 130then determines how the data blocks 2330 and parity block 2337 for eachparity group 2335 will be distributed 2470 in the disk array. At thispoint the client 110 sends or transmits data 2415 to the server node150, which receives and prepares the data 2420 for subsequent processingand storage. After receiving the data 2420, the server 130 calculatesthe parity blocks 2460 for each parity group 2335. Once the data blocks2330 and parity blocks 2337 have been obtained they are stored in thedisk array 2480 in a manner similar to that described with reference toFIG. 24A above.

In either method of data and parity information storage 2400, 2405, thetransfer of information from the client 110 may comprise both aparametric component and a data component. The parametric componentdefines a number of parameters used in the storage of information to thedisk array 2480 and may include for example: operation definitions, filehandles, offsets, and data lengths. When using the aforementionedstorage methods 2400, 2405 the parameters and data need not necessarilybe transferred at the same time. For example, the parameters may betransferred during the client storage request 2410 and the data may betransferred anytime thereafter in a subsequent stage of the method 2400,2405. In one aspect, transfer of information using the parametric anddata components desirably allows the distributed file storage system 100to make decisions about how to process the incoming data prior to theactual data transfer to thereby improve the flexibility andfunctionality of the system.

FIG. 25 illustrates another embodiment of the distributed file storagesystem 100 using a variable capacity disk array. The variable capacitydisk array incorporates a plurality of disks 2305 with potentiallynon-identical sizes whose space can be addressed and used for storingdata blocks 2330 and parity blocks 2337. Unlike conventional RAIDstorage systems that are limited by the capacity of the smallest drivewithin the disk array, the variable capacity disk array can contain anynumber or combination of disks and is not limited to accessing anaddress space boundary 2490 denoted by the smallest drive in the array.Using similar methods as described previously in conjunction with FIGS.23 and 24, the server 130 receives files 2320, 2340 and determines aparity group distribution for each file such that a plurality of datablocks 2330 and parity blocks 2337 are created. The data blocks 2330 andparity blocks 2337 are then distributed throughout the disk array 140 insuch a manner so as to avoid storing more than one block 2330, 2337 fromthe same parity group 2335 on a single disk 2305. The server 130 storesof these blocks 2330, 2337 across all of the available disk space, andthus is able to access disk space that lies beyond the boundary 2490defined by the smallest disk capacity (a typical storage boundary whichlimits conventional systems). As shown in FIG. 25, the distributed filestorage system 100 stores both data blocks 2330 and parity blocks 2337throughout the address space of each disk 2305 without boundarylimitations imposed by other disks within the array 140.

In addition to improved space utilization, a number of other importantfeatures arise from the aforementioned flexible distribution of theblocks 2330, 2337. In one aspect, using variable capacity disks 2305within the array 140 contributes to improved scalability andupgradeability of the distributed file storage system 100. For example,if the unused storage space within the array 140 fails below a desiredlevel, one or more of the disks within the array 140 can be readilyreplaced by higher capacity disks. The distributed file storage system100 implements an on-the-fly or “hot-swap” capability in which existingdisks within the array 140 can be easily removed and replaced by otherdisks. Since each server in a cluster maintains a copy of the metadatafor other servers in the cluster, servers can also be hot-swapped. Usingthis feature, a new higher capacity disk can be inserted into the array140 in place of a lower capacity disk. The server 140 is designed toautomatically incorporate the disk space of the newly inserted drive andcan further restore data to the new drive that resided on the formersmaller capacity drive. This feature of the distributed file storagesystem 100 provides for seamless integration of new disks into the array140 and facilitates disk maintenance and upgrade requirements.

In addition to exchanging or swapping existing disks 2305 within thearray 140, the server 130 can accommodate the addition of new disksdirectly into the array 140. For example, the disk array 140 containingthe fixed number of disks 2305 can be upgraded to include one or moreadditional disks such that the total number of disk in the array isincreased. The server 140 recognizes the additional disks andincorporates these disks into the addressable space of the distributedfile storage system 100 to provide another way for upgrading each diskarray 140.

In the examples shown above, both the swapping of disks to increasestorage space and the incorporation of additional disks into the arrayis facilitated by the flexible block placement and addressing of diskspace within the array 140. Unlike conventional systems that have arigid architecture where the number of disks within each array is fixedand the addressable disk space is dictated by the smallest disk withinthe array, the distributed file storage system 100 accommodates manydifferent disk array configurations. This flexibility is due, in part,to the manner in which the disk space is formatted, as well as, how thedata is arranged and processed by the server 130.

In one aspect, the flexibility of the distributed file storage system100 is improved through the use of parity groups 2335. In order toaccommodate files with different characteristics, as well as, improvehow information is distributed throughout the disk array 140, paritygroups 2335 are formed with variable block numbers. The block number ofthe parity group is defined by the number of blocks 2330, 2337 withinthe group. For example, a parity group containing 4 data blocks ischaracterized as having a block number of 4. In a similar manner, aparity group containing a single data block is characterized as having ablock number of 1. The block number of the parity group is one factorthat determines the size of the parity group and additionally determinesthe information that will be used to form the parity block.

FIG. 26A illustrates the formation of variable block number paritygroups in the distributed file storage system 100. In the illustratedembodiment, exemplary parity groups 2502, 2504 are shown with differentextents having 4 and 2 data blocks respectively. The server 130determines the number of data blocks 2330 associated with each group2502, 2504 and furthermore determines the distribution of each type ofparity group having specific block numbers that make up the total paritygroup distribution in the disk array 140. This feature of thedistributed file storage system 100 is discussed in connection withFIGS. 29 and 34.

Data organization and management by the server 130 is maintained usingone or more data structures that contain information which identifiesthe size and ordering of the data blocks 2330 within each parity group2502, 2504. In one embodiment, the ordering or sequence of the blocks2330, 2337 is maintained through a linked list organizational schema.The linked list contains one or more pointers that act as links 2505between each block 2330, 2337 within the parity group 2335. The links2505 therefore allow the server 130 to maintain knowledge of the orderof the blocks 2330, 2337 as they are distributed throughout the diskarray 140. As blocks are written to or read from the disk array 140, theserver 130 uses the links 2505 to identify the order of the blocks 2502,2504 used for each parity group 2335.

As shown in FIG. 26B, the distributed file storage system 100 can alsoallocate parity groups 2335 on the basis of block size. In theillustrated embodiment, exemplary parity groups 2506, 2508 are shownhaving the same block number of 4 with differing block sizes of 256K and128K respectively. The feature of variable block size allocation withineach parity group 2335 provides yet another way by which the server 130can distribute data and information within the disk array 140 in ahighly flexible and adaptable manner.

The implementation of parity groups having a plurality of differentblock numbers, as well as allowing for the use of different block sizeswithin each block, improves the ability of the server 130 to utilizeavailable disk space within the array 140. Furthermore, usingcombinations of different data block and parity group characteristicsallows the server to select combinations that are best suited forparticular data types.

For example, large data files such as multimedia video or sound are wellsuited for storage using large parity groups that contain large blocksizes. On the other hand, smaller files such as short text files do nothave the same space requirements as the larger file types and thus donot significantly benefit from storage in a similar block size. In fact,when small files are stored in large blocks, there is the potential forwasted space, as the smaller file does not use all of the spaceallocated to the block. Therefore, the distributed file storage system100, benefits from the ability to create data blocks 2330 and paritygroups 2335 of variable sizes to accommodate different data types andpermit their storage in a space-efficient manner.

As discussed in connection with FIGS. 14, the distributed file storagesystem 100 further improves the utilization of space within the diskarray 140 by implementing a mechanism for reorganizing the allocation ofdata blocks as needed to accommodate data stored to the disk array 140.Furthermore, a redistribution function (shown in FIG. 36) can alter thecomposition or distribution of blocks 2330, 2337 or parity groups 2335within the array 140 to make better use of available space and improveperformance by reorganizing information previously written to the array140.

In order to maintain coherence in the data stored to the disk array 140,knowledge of the size and ordering of each block within the parity group2335 is maintained by the server 130. Prior to writing of data to thedisk array 140, the server 130 creates a disk map that allocates all ofthe available space in the disk array 140 for storing particular blockssizes and/or parity group arrangements. Space allocation information ismaintained by the server 140 in a metadata structure known as a GeeTable. The Gee Table contains information used to identify the mappingand distribution of blocks within the disk array 140 and is updated asdata is stored to the disks 2305.

The Gee Table stores informational groups which interrelate andreference disk blocks or other discrete space allocation components ofthe disk array 140. These informational groups, referred to asGee-strings, contain disk space allocation information and uniquelydefine the location of files in the disk array 140. Each Gee-string issubdivided into one or more Gee-groups which is further divided into oneor more Gees containing the physical disk space allocation information.The Gee-strings and components thereof are interpreted by the server 130to define the mapping of parity groups 2335 in the disk array 140 whichstore information and files as will be discussed in greater detailhereinbelow.

Based on the available space within the disk array 140, the server 130determines the type and number of parity groups 2335 that will beallocated in the array 140. The initial parity group allocation prior todata storage forms the Gee Table and directs the storage of data basedon available parity groups. The Gee Table therefore serves as a map ofthe disk space and is updated as data is stored within the blocks 2330,2337 of the array 140 to provide a way for determining the fileallocation characteristics of the array 140. The server 130 retrievesstored files from the disk array 140 using the Gee Table as an indexthat directs the server 130 to the blocks 2330 where the data is storedso that they may be retrieved in a rapid and efficient manner.

FIG. 27 illustrates a portion of a Gee Table used to determine themapping of parity groups 2335 in the disk array 140. For additionaldetails of this architecture the reader is directed to sections whichrelate specifically to the implementation of the file system.

In one embodiment, space allocation in the disk array 140 is achievedusing a Gee Table 2530 containing an index field 2532, a G-code field2534, and a data field 2536. The index field 2532 is a value that isassociated with a row of information or Gee 2538 within the Gee Table2530 and is used as an index or a pointer into the array or listcomprising the Gee Table 2530. Additionally, the index field 2532uniquely identifies each Gee 2538 within the Gee Table 2530 so that itcan be referenced and accessed as needed.

The G-Code field 2534 indicates the type of data that is stored in thedisk space associated with each Gee 2538 and is further used to identifyspace allocation characteristics of the Gees 2538. During initializationof the disk array, the server 140 assigns all of the disk space withinthe array 140 to various parity groups 2335. These parity groups 2335are defined by the block size for data and parity blocks 2330, 2337 andthe number of data blocks within the group 2335. Identifiers in theG-Code field 2534 correspond to flags including “FREE”, “AVAL”, “SPARE”,“G-NODE”, “DATA”, “PARITY”, “LINK”, “CACHE-DATA”, or CACHE-PARITY”.

The data field 2536 stores data and information interpreted by theserver 130 in a specific manner depending upon the G-code fieldidentifier 2534. For example, this field can contain numerical valuesrepresenting one or more physical disk addresses defining the locationof particular blocks 2330, 2337 of the parity groups 2335. Additionally,the data field 2536 may contain other information that defines thestructure, characteristics, or order of the parity blocks 2335. As willbe described in greater detail hereinbelow, the information contained inthe G-table 2530 is accessed by the server 130 and used to store andretrieve information from the disk array 140.

In one embodiment, the fields 2532, 2534, 2536 of the G-table 2530 mapout how space will be utilized throughout the entire disk array 140 byassociating each physical block address with the designated Gee 2538.Parity groups 2335 are defined by sets of contiguous Gees 2538 that areheaded by the first Gee 2538 containing information that defines thecharacteristics of the parity group 2335. The G-Code field identifier“G-NODE” instructs the server 130 to interpret information in the datafield 2536 of a particular Gee 2538 having the “G-NODE” identifier asdefining the characteristics of a parity block 2335 that is defined by aG-group 2540.

A characteristic defined in the data field 2536 of the Gee 2538 having a“G-NODE” identifier includes an extent value 2542. The extent value 2542represents the extent or size of the blocks 2330, 2337 associated witheach Gee 2538 in a particular G-group 2540. The extent value 2542further indicates the number of logical disk blocks associated with eachfile logical block 2330, 2337. For example, the Gee with an index of“45” contains the G-Code identifier “G-NODE” and has a value of “2”associated with the extent value. This extent value 2542 indicates tothe server 130 that all subsequent data blocks and parity blocks definedin the parity group 2335 and represented by the G-group 2540 will have asize of 2 logical disk blocks. Thus, as indicated in FIG. 27, the Geeshaving indexes “46”-“49” are each associated with two logical addressesfor drive blocks within the array 140. In a similar manner, the Gee 2538with an index of “76” contains the G-Code identifier “G-NODE” and has anextent value of “3”. This value indicates to the server 130 that thesubsequent Gees “77”-“79” of the parity group are each associated with 3physical drive block addresses.

In the preceding discussion of FIG. 27, information is organized into asingle G-table however it will be appreciated that there are a number ofdifferent ways for storing the information to improve system flexibilityincluding the use of multiple tables or data structures. The exactmanner in which this information is stored is desirably designed toinsure that it may be efficiently accessed. For example, in oneembodiment nodes of the Gee Table 2530 can be utilized as a commonstorage vehicle for multiple types of metadata, including file names,identifiers (GNIDS), Gees, etc.

As discussed in connection with FIG. 29, other G-code identifiers areused during the storage and retrieval of information from the disk array140. For example, another G-code identifier, “DATA”, signifies that thedata field 2536 of a particular Gee 2538 is associated with the physicaladdress for one or more drive blocks that will store data. Likewise, theG-code identifier, “PARITY”, signifies that the data field 2536 of aparticular Gee is associated with the physical address for one or moredrive blocks that store parity information. The parity informationstored in the data blocks referenced by the “PARITY” Gee is calculatedbased upon the preceding “DATA” Gees as defined by the “G-NODE” Gee.Thus, as shown in the FIG. 27, the Gee 2538 having an index of “79” willstore the physical address of disk blocks that contain parityinformation for data blocks specified by Gees having indexes “77”-“78”.

FIG. 28 illustrates a process 2448 used by the server 130 to prepare thedisk array 140 for data storage. Preparation of the disk array 140commences with the server 130 identifying the characteristics 2550 ofeach disk 2305 within the array 140 to determine the quantity of spaceavailable. In one embodiment, the server 130 identifies physicalcharacteristics for the drives 2305 within the array 140. Thesecharacteristics can include: total drive number, individual drive size,sectors per disk, as well as other drive characteristics useful indetermining the available space of the disk array 140. To facilitate theconfiguration of the array 140, the server 130 can automatically detectand recognize the presence of each disk 2305 within the array 140 andcan electronically probe each disk 2305 to determine the drivecharacteristics. Alternatively, the server 130 can be programmed withinformation describing the array composition and drive characteristicswithout automatically determining this information from the array 140.

Upon acquiring the necessary information describing the arraycomposition, the server 130 determines a parity group allotment 2555 tobe used in conjunction with the available disk space. The parity groupallotment 2555 describes a pool of available parity groups 2335 that areavailable for data storage within the array 140. The parity groupallotment further describes a plurality of different block and/or paritygroup configurations each of which is suited for storing particular dataand file types (i.e. large files, small files, multimedia, text, etc).During data storage, the server 130 selects from the available pool ofparity groups 2335 to store data in a space-efficient manner thatreduces wasted space and improves data access efficiency.

In one embodiment, the parity group allotment is determinedautomatically by the server 130 based on pre-programmed parity groupdistribution percentages in conjunction with available disk space withinthe array 140. Alternatively, the server 130 can be configured to use aspecified parity group allotment 2555 that is provided to the server 130directly. In another aspect, the parity groups can be allocateddynamically by the server based on file characteristics such as filesize, access size, file type, etc.

Based on the allotment information and the disk space available in thearray 140, the server 130 performs a mapping operation 2560 to determinehow the parity groups 2335 of the allotment will be mapped to physicalblock addresses of drives 2305 within the array 140. The mappingoperation 2560 comprises determining a desirable distribution of paritygroups 2335 on the basis of their size and the available space andcharacteristics of the disk array 140. As the distribution of paritygroups 2335 is determined by the server 130, the G-table 2530 is createdand populated with Gees 2538 which associate each available parity group2335 with the physical block addresses defining their location on one ormore disks 2305 in the disk array 140. Initially, the G-table 2530describes parity groups 2335 that contain free or available space,however, as data is stored to the disk 2575, the G-table is updated toreflect the contents of the physical disk blocks that are pointed to bythe Gees 2538.

During operation of the distributed file storage system 100, the G-table2530 is accessed by the server 130 to determine the logical addresses offiles and information stored within the disk array 140. Furthermore,server 130 continually updates the G-table 2530 as information is savedto the disk array 140 to maintain knowledge of the physical location ofthe information as defined by the logical block addresses. Thedynamically updated characteristics of the G-Table 2530 data structuretherefore define and maintain the mapping of data and information in thedisk array 140.

In addition to the aforementioned a priori method of parity groupallocation other methods of disk preparation may also be utilized. Forexample, another method of disk preparation can use a set of free diskblock maps to allow dynamic allocation of the parity groups. This methodadditionally provides mechanisms for dynamic extension of existingparity groups and includes logic to ensure that the disk does not becomehighly fragmented. In some instances, fragmentation of the disk isundesirable because it reduces the ability to use long parity groupswhen mapping and storing information to the disk.

FIG. 29 illustrates one embodiment of a file storage schema 2600 thatuses the aforementioned parity group arrangements 2335 and G-table 2530to store information contained in an exemplary file 2605. The file 2605contains information coded by an electronic byte pattern that isreceived by the server 130 during client storage requests. In thestorage schema 2600, the file 2605 is divided into one or more filelogical blocks 2610 for storage. Each file logical block 2610 is storedin a cluster of one or more disk logical blocks 2615 in the disk array140. As previously indicated, the distributed file storage system 100retains many of the advantages of conventional storage systems,including the distribution of files across multiple disk drives and theuse of parity blocks to enhance error checking and fault tolerance.However, unlike many conventional systems, the distributed file storagesystem 100 does not restrict file logical blocks to one uniform size.File logical blocks of data and parity logical blocks can be the size ofany integer multiple of a disk logical block. This variability of filelogical block size increases the flexibility of allocating disk spaceand thus improves the use of system resources.

Referring to FIG. 29, the file 2605 is divided into a plurality of filelogical blocks 2610, each of which contains a portion of the informationrepresented in the file 2605. The number, size, and distribution of thefile logical blocks 2610 is determined by the server 130 by selectingavailable disk logical blocks 2615 designated in the G-table 2530. Theinformation contained in each file logical block 2610 is stored withinthe disk logical blocks 2615 and mapped using the G-table 2530. In thedistributed file storage system 100, the size of each file logical block2610 is described by the extent value 2542 which is an integer multiplein disk logical blocks 2615. For example, the logical block designated“LB-1” comprises two disk logical blocks 2615 and has an extent value of2. In a similar manner, the logical block designated “LB-7” comprisesthree disk logical blocks 2615 and has an extent value of 3.

The server 130 forms parity groups 2335 using one or more file logicalblocks 2615 and the associated parity block 2337. For each file 2605,one or more parity groups 2335 are associated with one another andordered through logical linkages 2617 (typically defined by pointers)used to determine the proper ordering of the parity groups 2335 to storeand retrieve the information contained in the file 2605. As shown in theillustrated embodiment, the file 2605 is defined by a parity string 2620containing four parity groups 2610. The four parity groups are furtherlinked by three logical linkages 2617 to designate the ordering of thelogical blocks “LB-1” through “LB-10” which make up the file 2605.

The G-table 2530 stores the information defining the G-string 2620 usinga plurality of indexed rows defining Gees 2538. The Gees 2538 define thecharacteristics of the G-strings 2620 and further describe the logicallocation of the associated file 2605 in the disk array 140. In theG-table 2530, the G-string 2620 is made up of the one or moreGee-groups. Each G-group is a set of contiguous Gees 2538 that allrelate to a single file. For example, in the illustrated embodiment, theGee-string 2620 includes three Gee-groups 2627, 2628 and 2629.

The first Gee in each G-group 2627-2629 is identified by the G-Codefield identifier “G-NODE” and the data field 2536 of this Gee containsinformation that defines the characteristics of a subsequent Gee 2632within the Gee-group 2627-2629. The data field 2536 of the first Gee ineach G-group 2627-2629 further contains information that determines theordering of the Gee-groups 2627-2629 with respect to one another. Someof the information typically found in the data field 2536 of the firstGee in each G-group 2627-2629 includes: A G-NODE reference 2635 thatrelates the current G-group with a file associated with a G-node at aparticular index (“67” in the illustration) in the G-table 2530; theextent value 2542 that defines the size of each file logical block 2610in terms of disk logical blocks 2615; and a root identifier 2637 thatindicates if the G-group is the first G-group in the G-string. Of aplurality of G-NODE Gees 2630, 2640, 2650, only the first Gee 2630contains an indication that it is a Root Gee, meaning that it is thefirst Gee of the Gee-string 2620.

Following the G-NODE Gee in a Gee-group are Gees representing one ormore distributed parity groups 2655-2658. A distributed parity group isset of one or more contiguous DATA Gees followed by an associated PARITYGee. A DATA Gee is a Gee with the G-code 2534 of “DATA” that lists disklogical block(s) where a file logical block is stored. For example, inFIG. 29, the Gees with indexes of 46-47, 50-52, 77-79 and 89-90 are allDATA Gees, and each is associated with one file logical block 2610.

A PARITY Gee is a Gee with the G-code 2534 of “PARITY.” Each PARITY Geelists disk logical block location(s) for a special type of file logicalblock that contains redundant parity data used for error checking anderror correcting one or more associated file logical blocks 2610. APARITY Gee is associated with the contiguous DATA Gees that immediatelyprecede the PARITY Gee. The sets of contiguous DATA Gees and the PARITYGees that follow them are known collectively as distributed paritygroups 2655-2658.

For example, in FIG. 29, the PARITY Gee at index 49 is associated withthe DATA Gees at indexes 46-48, and together they form the distributedparity group 2655. Similarly, the PARITY Gee at index 53 is associatedwith the DATA Gees at indexes 50-52, and together they form thedistributed parity group 2656. The PARITY Gee at index 79 is associatedwith the DATA Gees at indexes 77-78, which together form the distributedparity group 2657, and the PARITY Gee at index 91 is associated with theDATA Gees at indexes 89-90, which together form the distributed paritygroup 2658.

The size of a disk logical block cluster described by a DATA Gee or aPARITY Gee matches the extent listed in the previous G-NODE Gee. In theexample of FIG. 29, the G-NODE Gee 2630 of the first Gee-group 2627defines an extent size of 2, and each DATA and PARITY Gee of the twodistributed parity groups 2655, 2656 of the Gee-group 2627 lists twodisk logical block locations. Similarly, G-NODE Gee 2640 of the secondGee-group 2628 defines an extent size of 3, and each DATA and PARITY Geeof the Gee-group 2628 lists three disk logical block locations. G-NODEGee 2650 of the third Gee-group 2629 defines an extent size of 3, andeach DATA and PARITY Gee of the Gee-group 2629 lists three disk logicalblock locations.

If a Gee-group is not the last Gee-group in its Gee-string, then amechanism exists to link the last Gee in the Gee-group to the nextGee-group of the Gee-string using the logical linkages 2617. LINK Gees2660, 2661 both have the G-code 2534 of “LINK” and a listing in theirrespective Data fields 2536 that provides the index of the nextGee-group of the Gee-string 2620. For example, the Gee with an index of54 is the last Gee of Gee-group 2627, and its Data field 2536 includesthe starting index “76” of the next Gee-group 2628 of the Gee-string2620. The Gee with an index of 80 is the last Gee of Gee-group 2628, andits Data field 2536 includes the starting index “88” of the nextGee-group 2629 of the Gee-string 2620. Since the Gee-group 2629 does notinclude a LINK Gee, it is understood that Gee-group 2629 is the lastGee-group of the Gee-string 2620.

As previously indicated, the G-code 2534 of “FREE” (not shown in FIG.29) indicates that the Gee has never yet been allocated and has not beenassociated with any disk logical location(s) for storing a file logicalblock. The G-code 2534 of “AVAIL” (not shown in FIG. 29) indicates thatthe Gee has been previously allocated to a cluster of disk logicalblock(s) for storing a file logical block, but that the Gee is now freeto accept a new assignment. Two situations in which a Gee is assignedthe G-code of “AVAIL” are: after the deletion of the associated filelogical block; and after transfer of the file to another server in orderto optimize load balance for the distributed file storage system 100.

FIG. 30 illustrates a fault recovery mechanism 700 used by thedistributed file storage system 100 to maintain data consistency andintegrity when a data fault occurs. Data faults are characterized bycorruption or loss of data or information stored in one or more logicalblocks 2330 of the array 140. Each data fault can be furthercharacterized as a catastrophic event, where an entire disk 2305 failsrequiring all data on the failed disk to be reconstructed.Alternatively, the data fault can be characterized as a localized event,where the disk 2305 maintains operability but one or more physical disksectors or logical blocks become corrupted or damaged. In eitherinstance of the data fault, the distributed file storage system 100 usesa fault-tolerant restoration process to maintain data integrity.

FIG. 30 illustrates one embodiment of a fault-tolerant restorationprocess used to maintain data integrity in the distributed file storagesystem 100. As an example of how the process operates, a loss ofintegrity in a data block for a single parity group is shown. It will beappreciated that this loss of integrity and subsequent recoverymethodology can be applied to both instances of complete drive failureor localized data corruption. Thus, the restoration of informationcontained in a plurality of logical blocks can be accomplished usingthis process (i.e. restoring all data stored on a failed disk).Additionally, in instances where parity blocks become corrupted or lost,the information from each parity block can be restored in a similarmanner to the restoration process for data blocks using the remainingnon-corrupted blocks of the parity group.

In the illustrated embodiment the parity group 2335 includes two datablocks “DATA₁1” and “DATA₁2” and an associated parity block “PARITY₁1-2”and are shown stored on “DISK 2”, “DISK 8”, and “DISK 11” respectively.Knowledge of the logical disk addresses for each of these blocks ismaintained by the server 130 using the aforementioned G-table 2530. Aspreviously discussed, the G-table maintains mapping and structuralinformation for each parity group defined by the plurality of Gees 2538.The Gees further contain information including; the file descriptorassociated with the blocks of the parity group 2335, the size and extentof the blocks of the parity group 2335, and the mapping to the logicaldisk space for each block of the parity group 2335. During routineoperation, the server accesses data in the disks of the array using theG-table 2530 to determine the appropriate logical disk blocks to access.

As shown in FIG. 30, a complete disk failure is exemplified where a lossof data integrity 3072 results in the logical blocks on “DISK 8”becoming inaccessible or corrupted. During the fault tolerantrestoration process the server 130 determines that the data block“DATA,2” is among the one or more blocks that must be recovered 3074.Using conventional data/parity block recovery methods, the server 130recovers the compromised data block “DATA₁2” using the remaining blocks“DATA₁1” and “PARITY₁1-2” of the associated parity group 2335. Therecovered data block “DATA₁2-REC” is then stored to the disk array 140and contains the identical information that was originally contained in“DATA₁2”. Using the existing G-table mapping as a reference, the server130 identifies a new region of disk space that is available for storingthe recovered data block and writes the information contained in“DATA₁2-REC” to this region. In one embodiment, space for a new paritygroup is allocated and the reconstructed parity group is stored in thenew space. In another embodiment, the “old” parity group having 1 parityblock and N data blocks where one data block is bas, is entered onto thefree list as a parity group having N-1 data blocks. The server 130further updates the G-table 2530 to reflect the change in logical diskmapping (if any) of the recovered data block “DATA₁2-REC” to preservefile and data integrity in the disk array 140.

One desirable feature of the distributed file storage system 100 is thatthe recovered data block need not be restored to the same logical diskaddress on the same disk where the data failure occurred. For example,the recovered data block “DATA₁2-REC” can be stored to “DISK 3” and theG-table updated to reflect this change in block position. An importantbenefit resulting from this flexibility in data recovery is that thedisk array 140 can recover and redistribute data from a failed driveacross other available space within the disk array 140. Therefore, aportion of a disk or even an entire disk can be lost in the distributedfile storage system 100 and the data contained therein can be recoveredand moved to other locations in the disk array 140. Upon restoring thedata to other available disk space, the server 130 restores theintegrity of the parity group 2335 resulting in the preservation offault-tolerance through multiple losses in data integrity even withinthe same parity group without the need for immediate repair orreplacement of the faulted drive to restore fault-tolerance.

As an example of the preservation of fault tolerance through more thanone data fault, a second drive failure 3076 is shown to occur on “DISK2” and affects the same parity group 2335. This disk failure occurssubsequent to the previous disk failure in which “DISK 8” is illustratedas non-operational. The second disk failure further results in the lossof data integrity for the block “DATA₁1”. Using the method of datarecovery similar to that described above, the information contained inthe data block “DATA₁1” can be recovered and redistributed 3078 toanother logical address within the disk array 140. The recovered datablock “DATA₁1-REC” is illustrated as being saved to available disk spacelocated on “DISK 5” and is stored in a disk region free of corruption ofdata fault. Thus, fault tolerance is preserved by continuous datarestoration and storage in available non-corrupted disk space.

The fault tolerant data recovery process demonstrates an example of howthe distributed file storage system 100 handles data errors orcorruption in the disk array 140. An important distinction between thissystem 100 and conventional storage systems is that the aforementioneddata recovery process can automatically redistribute data or parityblocks in a dynamic and adaptable manner. Using block redistributionprocesses described above results in the distributed file storage system100 having a greater degree of fault-tolerance compared to conventionalstorage systems. In one aspect, the increase in fault tolerance resultsfrom the system's ability to continue normal operation even when one ormore drives experience a data loss or become inoperable.

In conventional storage systems, when a single disk failure occurs, thestorage system's fault tolerant characteristics are compromised untilthe drive can be repaired or replaced. The lack of ability ofconventional systems to redistribute data stored on the faulted drive toother regions of the array is one reason for their limited faulttolerance. In these conventional systems, the occurrence of a seconddrive failure (similar to that shown in FIG. 30) will likely result inthe loss or corruption of data that was striped across both of thefailed drives. The distributed file storage system 100 overcomes thislimitation by redistributing the data that was previously stored on thefaulted drive to a new disk area and updating the G-table which storesthe mapping information associated with the data to reflect its newposition. As a result, the distributed file storage system 100 isrendered less susceptible to sequential drive faults even if it occurswithin the same parity group. Thus, the process of recovery andredistribution restores the fault-tolerant characteristics of thedistributed file storage system 100 and beneficially accommodatesfurther drive failures within the array 140.

Another feature of the distributed file storage system 100 relates tothe flexible placement of recovered data. In one aspect, a recovereddata block may be stored anywhere in the DFSS through a modification ofthe parity group associated with the data. It will be appreciated thatplacement of recovered data in this manner is relatively simple andefficient promoting improved performance over conventional systems.

In one embodiment, this feature of tolerance to multiple disk failuresresults in an improved “hands-off” or “maintenance-free” data storagesystem where multiple-drive failures are tolerated. Furthermore, thedistributed file storage system 100 can be configured with theanticipation that if data corruption or a drive failure does occur, thesystem 100 will have enough available space within the array 140 torestore and redistribute the information as necessary. This improvedfault tolerance feature of the distributed file storage system 100reduces maintenance requirements associated with replacing or repairingdrives within the array. Additionally, the mean time between failure(MTBF) characteristics of the system 100 are improved as the system 100has reduced susceptibility to sequential drive failure or datacorruption.

In one embodiment the distributed file storage system is desirablyconfigured to operate in a “hands-off” environment where the disk arrayincorporates additional space to be tolerant of periodic data corruptionor drive failures without the need for maintenance for such occurrences.Configuration of the system 100 in this manner can be more convenientand economical for a number of reasons such as: reduced futuremaintenance costs, reduced concern for replacement drive availability,and reduced downtime required for maintenance.

In one aspect, the fact that parity groups may be integrated with thefile metadata provides a way for prioritizing recovery of the data. Forexample, when some file or set of files is designated as highlyimportant, or is frequently accessed, a background recovery process canbe performed on those designated files first. In the case where the fileis frequently accessed, this feature may improve system performance byavoiding the need for time-consuming on-demand regeneration when aclient attempts to access the file. In the case where the file is highlyimportant, this feature reduces the amount of time where a second drivefailure might cause unrecoverable data loss.

FIG. 31 illustrates one embodiment of a method 3172 for recoveringcorrupted or lost data resulting from one or more data faults. Asdiscussed above and shown the previous figure, data corruption can occuras a result of a complete drive failure or data corruption can belocalized and affect only a limited subset of logical storage blockswithin the array. The distributed storage system identifies the presenceof data corruption in a number of ways. In one aspect, the serverrecognizes corrupted data during storage or retrieval operations inwhich the one or more of the disks of the array are accessed. Theseoperations employ error checking routines that verify the integrity ofthe data being stored to or retrieved from the array. These errorchecking routines typically determine checksum values for the data whileperforming the read/write operation to insure that the data has beenstored or retrieved in a non-corrupted manner. In cases where theread/write operation fails to generate a valid checksum value, theread/write operation may be repeated to determine if the error wasspurious in nature (oftentimes due to cable noise or the like) or due toa hard error where the logical disk space where the data is stored hasbecome corrupted.

Data corruption may further be detected by the server 130 when one ormore disks 2305 within the array 140 become inaccessible.Inaccessibility of the disks 2305 can arise for a number of reasons,such as component failure within the drive or wiring malfunction betweenthe drive and the server. In these instances where one or more diskswithin the array are no longer accessible, the server 130 identifies thedata associated with the inaccessible drive(s) as being corrupted orlost and requiring restoration.

During the identification of the data fault 3175, the number andlocation of the affected logical blocks within the disk array 140 isdetermined. For each logical block identified as corrupted or lost, theserver 130 determines the parity group associated with the corrupteddata 3177. Identification of the associated parity group 2335 allows theserver 130 to implement restoration procedures to reconstruct thecorrupted data using the non-corrupted data and parity blocks 2330, 2337within the same parity group 2335. Furthermore, the logical storageblock or disk space associated with the corrupted data is identified3179 in the G-table 2530 to prevent further attempts to use thecorrupted disk space.

In one embodiment, the server 130 identifies the “bad” or corruptedlogical blocks mapped within the G-table 2530 and removes the associatedGees from their respective parity groups thereby making the parity groupshorter. Additionally, the server 130 can identify corrupted logicalblocks mapped within the G-table 2530 and remap the associated paritygroups to exclude the corrupted logical blocks.

Prior to restoring the information contained in the affected logicalblocks, the server 130 determines the number and type of parity groupsthat are required to contain the data 3180 that will subsequently berestored. This determination 3180 is made by accessing the G-table 2530and identifying a suitable available region within the disk array 140based on parity group allocation that can be used to store thereconstructed data. When an available parity group is found, the server130 updates the G-table 2530 to reflect the location where thereconstructed data will be stored. Additionally, the mapping structureof the array 140 is preserved by updating the links or referencescontained in Gees 2538 of the G-table 2530 to reflect the position andwhere the reconstructed data will be stored in relation to other paritygroups of the parity string. Data is then restored 3181 to the logicaldisk address pointed to by the updated Gee using the remainingnon-corrupted blocks of the parity group to provide the informationneeded for data restoration.

As previously discussed, one feature of the distributed file storagesystem 100 is the use of variable length and/or variable extent paritygroups. Unlike conventional storage systems that use only a fixed blocksize and configuration when storing and striping data to a disk array,the system 100 of the present invention can store data in numerousdifferent configurations defined by the parity group characteristics. Inone embodiment, by using a plurality of different parity groupconfigurations, the distributed file storage system 100 can improve theefficiency of data storage and reduce the inefficient use of disk space.

FIGS. 32A, B illustrate a simplified example of the use of variablysized parity groups to store files with different characteristics. Asshown in FIG. 32A, File #1 comprises a 4096 byte string that is storedin the disk array 140. As previously discussed, the server 130, selectsspace from the plurality of parity groups 2335 having differentstructural characteristics to store the data contained in File #1. Inthe illustrated embodiment, 4 exemplary parity strings 3240-3243 areconsidered for storing File #1. Each of the parity strings 3240-3243comprises one or more parity groups 2335 that have a designated extentbased on a logical disk block size of 512 bytes. The parity groups 2335of each parity string 3240-3243 are further associated using the G-table2530 which link the information in the parity groups 2335 to encode thedata contained in File #1.

The first parity string 3240 comprises a single 4-block parity grouphaving 1024-byte data and parity blocks. The total size of the firstparity string 3240 including all data and parity blocks is 5120 bytesand has an extent value of 2. The second parity string 3241 comprisestwo 3-block parity groups having 1024-byte data and parity blocks. Thetotal size of the second parity string 3241 including the data andparity blocks is 8192 bytes and has an extent value of 2. The thirdparity string 3242 comprises four 2-block parity groups having 512-bytedata and parity blocks. The total size of the third parity string 3242including the data and parity blocks is 6144 bytes and has and extentvalue of 1. The fourth parity string 3243 comprises nine 1-block paritygroups having 512-byte data and parity blocks. The total size of thefourth parity string 3243 including the data and parity blocks is 8192bytes and has an extent of 1.

Each of the parity strings 3240-3243 represent the minimum number ofparity groups 2335 of a particular type or composition that can be usedto fully store the information contained in File #1. One reason for thedifference in parity group composition results from the differentnumbers of total bytes required to store the data contained in File #1.The differences in total byte numbers further result from the number andsize of the parity blocks 2337 associated with each parity group 2335.

A utilization value 3245 is shown for each parity string 3240-3242 usedto store File #1. The utilization value 3245 is one metric that can beused to measure the relative efficiency of storage of the data of File#1. The utilization value 3245 is determined by the total number ofbytes in the parity string 3240-3242 that are used to store the data ofFile #1 compared to the number of bytes that are not needed to store thedata. For example, in the second parity string 3241, one parity group3247 is completely occupied with data associated with File #1 whileanother parity group 3246 is only partially utilized. In one aspect, theremainder of space left in this parity group 3246 is unavailable forfurther data storage due to the composition of the parity group 3246.The utilization value is calculated by dividing the file-occupying orused byte number by the total byte number to determine a percentagerepresentative of how efficiently the data is stored in the paritystring 3240-3243. Thus, the utilization values for the first, second,third, and fourth parity strings 3240-3243 are 100%, 66%, 100%, and 100%respectively.

In one embodiment, the server 130 determines how to store data based onthe composition of the file and the availability of the different typesof parity groups. As shown in FIG. 32A, of the different choices forstoring File #1, the first parity string 3240 is most efficient as ithas the lowest total bytes required for storage (5120 bytes total), aswell as, a high utilization value (100%). Each of the other paritystrings 3241-3243 are less desirable for storing the data in File #1 dueto greater space requirements (larger number of total bytes) and in somecases reduced storage efficiency (lower utilization value).

FIG. 32B illustrates another simplified example of the use of variablysized parity groups to store files of differing sizes. In theillustrated-embodiment the storage characteristics of a plurality offour parity strings 3250-3253 are compared for a small file comprising asingle 1024 byte string. The parity strings comprise: The first paritystring 3250 composed of the single parity group 2335 having 4 datablocks 2330 and 1 parity block 2337, each 1024 bytes in length; Thesecond parity string 3251 composed of the single parity group 2335having 3 data blocks 2330 and 1 parity block 2337, each 1024 bytes inlength; The third parity string 3251 composed of the single parity group2335 having 2 data blocks 2330 and 1 parity block 2337, each 512 bytesin length; and The fourth parity string 3253 having two parity groups2335 each composed of the single 512-byte data block 2330 and the parityblock 2337.

When storing the byte pattern contained in File #2 different storagecharacteristics are obtained for each parity string 3250-3253. Forexample, the first parity string 3250 is only partially occupied by thedata of File #2 resulting in the utilization value 3245 of 25%.Similarly, the second parity string 3251 is also partially occupiedresulting in the utilization value 3245 of 33%. Conversely, the thirdand fourth parity strings 3252-3253 demonstrate complete utilization ofthe available space in the parity group (100% percent utilization).Based on the exemplary parity group characteristics given above, themost efficient storage of File #2 is achieved using the third paritystring 3252 where a total of 1536 bytes are allocated to the paritystring with complete (100%) utilization.

The aforementioned examples demonstrate how files with differing sizescan be stored in one or more parity group configurations. In each of theabove examples, the unused blocks or partially filled blocks remainingin the parity group are “zero-filled” or “one-filled” to complete theformation of the parity group and encode the desired information fromthe file. Furthermore, by providing a plurality of parity groupconfigurations, improved storage efficiency can be achieved fordifferent file sizes where less space is left unutilized within the diskarray 140. It will be appreciated by one of skill in the art that manypossible parity group configurations can be formed in a manner similarto those described in FIGS. 32A, B. Examples of characteristics whichmay influence the parity group configuration include: logical blocksize, extent, parity group size, parity group number, among othercharacteristics of the distributed file storage system 100. Therefore,each of the possible variations in parity group characteristics anddistribution should be considered but other embodiments of the presentinvention.

Typically, one or more selected parity groups of the availableconfigurations of parity groups provide improved storage efficiency forparticular file types. Therefore, in order to maintain storageefficiency across each different file configuration a plurality ofparity group configuration are desirably maintained by the server. Onefeature of the distributed file storage system 100 is to identifydesirable parity group configurations based on individual filecharacteristics that lead to improved efficiency in data storage.

FIG. 33 illustrates one embodiment of a data storage process 3360 usedby the distributed file storage system 100 to store data. This process3360 desirably improves the efficiency of storing data to the disk array140 by selecting parity group configurations that have improvedutilization characteristics and reduce unused or lost space. In thisprocess 3360 the server 130 receives files 3361 from the clients 110that are to be stored in the disk array 140. The server 130 thenassesses the file's characteristics 3363 to determine suitable paritystring configurations that can be used to encode the informationcontained in the file. During the file assessment 3363, the server 130can identify characteristics such as the size of the file, the nature ofthe data contained in the file, the relationship of the file to otherfiles presently stored in the disk array, and other characteristics thatare used to determine how the file will be stored in the disk array 140.Using the G-table 2530 as a reference, the server 130 then identifies3365 available (free) parity groups that can be used to store the fileto the disk array 140.

Typically, a plurality of parity group configurations are available andcontain the requisite amount of space for storing the file. Using ananalysis methodology similar to that described in FIGS. 32A, B, theserver 130 assesses the utilization characteristics for each paritygroup configuration that can be used to store the file. Based on theavailable configurations and their relative storage efficiency, theserver 130 selects a desirable parity group configuration 3367 to beused for file storage. In one embodiment, a desirable parity groupconfiguration is identified on the basis of the high utilization value3245 that is indicative of little or no wasted space (non-file encodingspace) within the parity groups. Furthermore, a desirable parity groupconfiguration stores the file in the parity string 2335 comprising theleast number of total bytes in the parity string. Using these twoparameters as a metric, the server 130 selects the desirable paritygroup configuration 3367 and stores the data contained in the file 3369.During file storage 3369, the G-table 2530 is updated to indicate howthe file is mapped to the disk array 140 and characteristics of theG-string 2530 used to store the file are encoded in the appropriate Geesof the G-table 2530. Furthermore, the one or more Gees corresponding tothe logical disk blocks where the data from the file is stored areupdated to reflect their now occupied status (i.e. removed from pool ofavailable or free disk space).

In another embodiment the distributed file storage system 100 provides aflexible method for redistributing the parity groups 2335 of the diskarray 140. As discussed previously, prior to storage of information inthe disk array 140 the distributed file storage system 100 creates theG-table 2530 containing a complete map of the logical blocks of eachdisk 2305 of the disk array 140. Each logical block is allocated to aparticular parity group type and may be subsequently accessed duringdata storage processes when the group type is requested for datastorage. During initialization of the disk array 140, the server 130allocates all available disk space to parity groups 2335 of variouslengths or sizes which are subsequently used to store data andinformation. As files are stored to the disk array 140, the paritygroups 2335 are accessed as determined by the server 130 and theavailability of each parity group type changes.

Using the plurality of different sizes and configurations of paritygroups 2335 allows the server 130 to select particular parity groupconfigurations whose characteristics permit the storage of a widevariety of file types with increased efficiency. In instances where afile is larger than the largest available parity group, the server 130can break down the file and distribute its contents across multipleparity groups. The G-table 2530 maps the breakdown of file informationacross the parity groups over which it is distributed and is used by theserver 130 to determine the order of the parity groups should beaccessed to reconstruct the file. Using this method, the server 140 canaccommodate virtually any file size and efficiently store itsinformation within the disk array 140.

When a large quantity of structurally similar data is stored to the diskarray 140, a preferential parity group length can be associated with thedata due to its size or other characteristics. The resulting storage inthe preferential parity group length reduces the availability of thisparticular parity group and may exhaust the supply allocated by theserver 130. Additionally, other parity group lengths can becomeunderutilized, as the data stored to the disk array 140 does not utilizethese other parity group types in a balanced manner. In one embodimentthe distributed file storage system 100 monitors the parity setdistribution and occupation characteristics within the disk array 140and can alter the initial parity set distribution to meet the needs ofclient data storage requests on an ongoing basis and to maintain abalanced distribution of available parity group types. The parity groupmonitoring process can further be performed as a background process orthread to maintain data throughput and reduce administrative overhead inthe system 100.

FIGS. 34A-C illustrate a simplified parity set redistribution processuseful in maintaining availability of parity groups 2335 within the diskarray 140. Redistribution is handled by the server 130, which can updatesets of Gees of the G-table 2530 to alter their association with a firstparity group into an association with a second parity group.Furthermore, other characteristics of the data and parity blocks withina parity group can be modified, for example, to change the size orextent of each block. By updating the G-table 2530, the server 140provides a parity group balancing functionality to insure that each typeor configuration of parity group is available within the disk array 140.

FIG. 34A illustrates an exemplary parity group distribution for the diskarray 140 prior to storage of data from clients 110. The parity groupdistribution comprises four types of parity groups corresponding to a4-block parity group 3480, a 3-block parity group 3481, a 2-block paritygroup 3482, and a 1-block parity group 3483. In configuring thedistributed file storage system 100 there is an initial allocation 3491of each type of parity group 3480-3483. For example, in the illustratedembodiment, 10000 groups are allocated for each type of parity group3480-3483. Each parity group 3480-3483 further occupies a calculablepercentage of a total disk space 3485 within the disk array 140 based onthe size of the parity group. Although the parity group distribution isillustrated as containing four types of parity groups, it will beappreciated by one of skill in the art that numerous other sizes andconfigurations of parity groups are possible. (e.g. 8, 10, 16, etc.) Inone embodiment, the number of blocks within the parity group 2335 can beany number less than or equal to the number of disks within the diskarray 140. Furthermore, the parity groups 2335 may be distributed acrossmore than one disk array 140 thus allowing for even larger parity groupblock numbers that are not limited by the total number of disks withinthe single disk array 140.

As disk usage occurs 3487, parity groups 3480-3483 become occupied withdata 3490 and, of the total initial allocation of parity groups 3491, alesser amount remain as free or available parity groups 3492. FIG. 34Billustrates parity group data occupation statistics where of theoriginal initially allocated parity groups 3491 for each parity type, afraction remain as free or available 3492 for data storage. Morespecifically: The occupation statistics for the 4-block parity groupcomprise 2500 free vs. 7500 occupied parity groups, the occupationcharacteristics for the 3-block parity group comprise 7500 free vs. 2500occupied parity groups, the occupation characteristics for the 2-blockparity group comprise 3500 free vs. 6500 occupied parity groups, and theoccupation characteristics for the 1-block parity group comprise 500free vs. 9500 occupied parity groups.

During operation of the distributed file storage system 100, free paritygroups can become unevenly distributed such that there are a greaterproportion of free parity groups in one parity group length and a lesserproportion of free parity groups in another parity group length. Whilethis disparity in distribution does not necessarily impact theperformance or effectiveness of storing data to the disk array 140, theserver 130 monitors the availability of each parity group 3480-3483 toinsure that no single parity group type becomes completely depleted.Depletion of a parity group is undesirable as it reduces the choicesavailable to the server 130 for storing data and can potentially affectthe efficiency of data storage. As shown in FIG. 34B, the 3-block paritygroup 3481 possess a greater number of free parity groups 3492 comparedto any of the other parity groups 3480, 3482, 3483 while the 1-blockparity group 3483 possess the smaller number of free parity groups andmay be subject to complete depletion should data storage continue with asimilar parity group distribution characteristics.

To prevent parity group depletion, the server 130 can redistribute orconvert 3494 at least a portion of one parity group into other paritygroup lengths. As shown in FIG. 34C, the server 130 converts a portionof the 3-block parity group 3481 into the 1-block parity group 3483. Theresulting conversion redistributes the number of parity groups withinthe disk array 140 by reducing the number of parity groups of a firstparity group type (3-block parity) and generates an additional quantityof parity groups of the second parity group type (1-block parity).Redistribution in this manner beneficially prevents the completedepletion of any parity group and thus preserves the efficiency of datastorage by insuring that each parity group is available for datastorage.

In one embodiment, parity group redistribution is performed by updatingone or more Gees of the G-table 2530 to reflect new parity groupassociations. As previously discussed, each parity group 2335 isassigned using a data structure linking associated Gees. Theredistribution process updates these data structures to redefine theparity group associations for the logical blocks of the disk array 140.Thus, the server 130 can rapidly perform parity group distributionwithout affecting existing occupied parity groups or significantlydegrading the performance of the distributed file storage system 100.

FIGS. 35A, B illustrate two types of parity group redistributionprocesses 3500 that are used by the system 100 to maintain parity groupavailability in the disk array 140. A first redistribution process knownas parity group dissolution 3510 converts a larger parity group into oneor more smaller parity groups. As shown in FIG. 35A, a 5-block paritygroup 3515 can be converted into two smaller parity groups consisting ofa 1-block parity group 3520 and a 3-block parity group 3525. The 5-blockparity group 3515 can also be converted into two 2-block parity groups3530 or alternatively three 1-block parity groups 3520.

A second redistribution process 3500 known as parity group consolidation3535 (shown in FIG. 35B) converts two or more smaller parity groups intoone or more larger parity groups. For example, two 2-block parity groups3530 can be combined to form the single 5-block parity group 3515.Alternatively, the two 2-block parity groups 3530 can be combined toform a 3-block parity group 3525 and a 1-block parity group 3525.

It will be appreciated that numerous combinations of parity groupdissolution 3510 and consolidation 3535 exist. These redistributionprocesses 3500 are advantageously used to modify the existing paritygroup configurations to accommodate the demands of the system 100 as itis populated with information. Using these processes 3500 improves theperformance and efficiency of storing data in the system 100.Consistency and knowledge of the parity group distribution is maintainedusing the G-table 2530 which is updated as the modifications to theparity groups are made. These processes 3500 can further be performedusing both occupied and unoccupied parity groups or a combinationthereof to further improve the flexibility of the distributed storagesystem 100.

FIG. 36 illustrates a process 3600 used by the server 130 to monitorparity group availability and perform parity group redistribution asneeded. This process 3600 is important in maintaining a desirablequantity of each type of parity group so that files can be stored withimproved storage efficiency. In the illustrated embodiment, the process3600 commences with a monitoring function that determines parity groupavailability 3602. The monitoring function 3602 can be performedcontinuously or at periodic time intervals to insure available paritygroups remain balanced within the disk array 140. Using the G-table 2530as a reference, the monitoring function 3602 rapidly assesses thecurrent status of data occupation within the array 140. Morespecifically, the monitoring function 3602 can determine theavailability of each type of parity group and determine the number offree or available groups using the mapping information of the G-table2530.

As a particular type of parity group is depleted 3604, indicated by areduction in the number of free parity groups for the particular grouptype, the server 130 proceeds to assess the parity group statistics 3606for each parity group defined within the G-table 2530. The assessment ofparity group statistics 3606 comprises determining both the free andavailable parity group statistics using the G-table 2530 as a reference.In determining how to increase the quantity of free parity groups for adepleted parity group type, the server 130 assesses which other paritygroups contain available or free parity groups that have not be used tostore data. This assessment is made based upon the parity group usagestatistics which, for example, indicate free parity groups, occupiedparity group, disk space occupation, frequency of access or utilization,among other statistics that can be collected while the distributed filestorage system 100 is in operation.

In one embodiment, the server 130 continually collects and stores usagestatistics so as to provide up-to-date and readily available statisticalinformation that can be used to determine how redistribution ofavailable parity groups should proceed. Additionally, these statisticscan be acquired from the G-table 2530 where the server 130 calculatesthe usage statistics based upon the current contents of the G-table2530.

Upon acquiring the parity group statistics 3606, the server 130calculates a suitable re-distribution 3608 of the parity groups. There-distribution 3608 desirably takes into account factors such as, forexample, the number and type of parity groups 2335 within the disk array140, the availability of unoccupied parity groups within each paritygroup type, the frequency of usage or access of each parity group type,among other considerations that can be determined using the parity groupstatistics. During parity group redistribution 3608, one or moredifferent parity groups can be used as a source for supplementing thedepleted parity group set. The overall effect of redistribution 3608 isto balance the free or available parity groups of each type so that noone single parity group is depleted.

Parity group redistribution in the aforementioned manner is facilitatedby the use of the G-table 2530 mapping structure. Using the G-table2530, parity groups can be readily assigned and re-assigned withoutsignificant overhead by modifying the contents of appropriate Gees. Thismethod of disk space allocation represents a significant improvementover conventional disk storage methods such as those used in RAIDarchitectures. In conventional RAID architectures, the rigid nature ofdisk space allocation prevents optimizing data storage in the mannerdescribed herein. Furthermore, the parity group redistribution featureof the distributed file storage system 100 provides an effective methodto monitor and maintain optimized disk storage characteristics withinthe array to insure efficient use of available disk space.

In addition to redistributing free or available space within the diskarray 140, the distributed file storage system 100 also features amethod by which occupied parity groups can be modified and re-configuredinto other parity group types. One benefit realized by re-configuringoccupied parity groups is that unnecessary space allocated to aparticular parity group in which data is stored may be reclaimed for useand converted to available or free storage space. Furthermore,re-configuration of occupied parity groups can be used to de-fragment orconsolidate the information stored in the disk array 140 enabling theinformation contained therein to be accessed more efficiently.

FIG. 37 illustrates one embodiment of a parity groupoptimization/de-fragmentation routine used to re-configure data withinthe disk array 140. Parity group occupation statistics are shown fordifferent parity lengths including: a 1-block parity group having 2800free parity groups and 7200 occupied parity groups, a 2-block paritygroup having 1800 free parity groups and 8200 occupied parity groups, a3-block parity group having 800 free parity groups and 9200 occupiedparity groups, and a 4-block parity group having 2300 free parity groupsand 7700 occupied parity groups.

When the server 130 performs an optimization routine 3785, one or moreof the parity groups can be re-configured into another type of paritygroup. For example, as shown in the illustration, a portion of the1-block parity groups corresponding to 3200 groups can be consolidatedinto 2000 groups of 4-block parity. In the consolidated parity groups,the original information contained in the 1-block parity group isretained in a more compact form in the 4-block parity groups. Theresulting 4-block parity groups require less parity information tomaintain data integrity compared to an equivalent quantity ofinformation stored in a 1-block parity configuration. In the illustratedembodiment, the residual space left over from the optimization routinecorresponds to approximately 1200 groups of 1-block parity and can bereadily converted into any desirable type of parity group using G-tableupdating methods.

The aforementioned optimization routine can therefore beneficiallyre-allocate occupied logical disk blocks into different parity groupconfigurations to reclaim disk space that might otherwise be lost orrendered inaccessible due to the manner in which the data is stored inthe parity groups. As with other parity group manipulation methodsprovided by the distributed file storage system 100, the process ofoptimizing parity groups is readily accomplished by rearrangement of themapping assignments maintained by the G-table 2530 and provides asubstantial improvement in performance compared to conventional storagesystems. In conventional systems, data restriping is a time consumingand computationally expensive process that reduces data throughput andcan render the storage device unavailable while the restriping takesplace.

Like conventional storage systems, the distributed file storage system100 provides complete functionality for performing routine data and diskoptimization routines such as de-fragmentation of logical blockassignments and optimization of data placement to improve access timesto frequently accessed data. These processes are efficiently handled bythe system 100, which can use redundant data access to insureavailability of data disk optimization routines take place.

The distributed file storage system 100 further provides adaptive loadbalancing characteristics that improve the use of resources includingservers 130 and disk arrays 140. By balancing the load between availableresources, improved data throughput can be achieved where clientrequests are routed to less busy servers 130 and associated disk arrays140. Load-dependent routing in this manner reduces congestion due tofrequent accessing of a single server or group of servers. Additionaldetails of these features can be found in those discussions relating toadaptive load balancing and proactive control of the DFSS 100.

In one embodiment, frequently accessed data or files are automaticallyreplicated such that simultaneous requests for the same information canbe serviced more efficiently. Frequently accessed data is identified bythe servers 130 of the distributed file storage system 100, whichmaintain statistics on resource usage throughout the network.Furthermore, the servers 130 can use the resource usage statistics inconjunction with predictive algorithms to “learn” content accesspatterns. Based on these access patterns frequently accessed content canbe automatically moved to server nodes 150 that have high bandwidthcapacities capable of serving high numbers of client requests.Additionally, less frequently accessed material can be moved to servernodes 150 that have higher storage capacities or greater availablestorage space where the data or files can be conveniently stored inareas without significant bandwidth limitations.

FIG. 38 illustrates one embodiment of a load balancing method 3800 usedin conjunction with the distributed file storage system 100 to provideimproved read/write performance. In the load balancing method 3800, fileoperations are performed 3851 and file access statistics arecontinuously collected 3852 by the servers 130. These statistics includeinformation describing file access frequencies, file sizecharacteristics, file type characteristics, among other information.Resource utilization statistics are also collected 3854 and containinformation that characterize how data is stored within the distributedfile storage system 100. The resource utilization statistics identifyhow each disk array 140 is used within the system 100 and may containstatistics that reflect the amount of free space within the array, theamount of used space within the array, the frequency of access of aparticular disk within the disk array, the speed of servicing clientrequests, the amount of bandwidth consumed servicing client requests andother statistics that characterize the function of each disk array 140within the distributed file storage system 100. The resource utilizationstatistics can also be used to evaluate the statistics across multipledisk arrays to determine how each disk array compares to other diskarrays within the distributed file storage system 100. This informationis useful in identifying bandwidth limitations, bottlenecks, disk arraysoverloads, and disk array under utilization.

Using either the resource utilization statistics 3854, the file accessstatistics 3852, or a combination thereof, the one or more servers 130of the distributed file storage system 100 predict future file andresource utilization characteristics 3856. In one embodiment, the futurefile and resource utilization characteristics 3856 describe a predictedworkload for each of the disk arrays within the distributed file storagesystem 100. The predicted workload serves as a basis for determining howto best distribute the workload 3858 among available servers and diskarrays to improve access times and reduce bandwidth limitations.Furthermore, the predicted workload can be used to distribute files orcontent 3860 across the available disk arrays to balance futureworkloads.

An additional feature of the distributed file storage system 100 is theability to perform “hot upgrades” to the disk array 140. This processcan involve “hot-swapping” operations where an existing disk within thearray is replaced (typically to replace a faulted or non-operationaldrive). Additionally, the “hot upgrade” process can be performed to adda new disk to the existing array of disks without concomitant diskreplacement. The addition of the new disk in this manner increases thestorage capacity of the disk array 140 automatically and eliminates theneed to restrict access to the disk array 140 during the upgrade processin order to reconfigure the system 100. In one embodiment, the server130 incorporates the additional space provided by the newly incorporateddisk(s) by mapping the disk space into existing unused/available paritygroups. For example, when a new drive is added to the disk array 140,the server 130 can extend the length or extent of each available paritygroup by one. Subsequently, parity group redistribution processes can beinvoked to optimize and distribute the newly acquired space in a moreefficient manner as determined by the server 130. In one embodiment,when there are more newly added logical disk blocks than can beaccommodated by addition to the unused parity groups, at least some ofthe unused parity groups are split apart by the dissolution process tocreate enough unused parity groups to incorporate the newly addedlogical disk blocks.

Load Balancing

One approach to adaptive or active load balancing includes twomechanisms. A first mechanism predicts the future server workload, and asecond mechanism reallocates resources in response to the predictedworkload. Workload prediction can have several aspects. For example, oneaspect includes past server workload, such as, for example, file accessstatistics and controller and network utilization statistics. Theloading prediction mechanism can use these statistics (with anappropriate filter applied) to generate predictions for future loading.For example, a straightforward prediction can include recognizing that afile that has experienced heavy sequential read activity in the past fewminutes will likely continue to experience heavy sequential read accessfor the next few minutes.

Predictions for future workload can be used to proactively manageresources to optimize loading. Mechanisms that can be used to reallocateserver workload include the movement and replication of content (filesor objects) between the available storage elements such that controllerand storage utilization is balanced, and include the direction of clientaccesses to available controllers such that controller and networkutilization is balanced. In one embodiment, some degree of cooperationfrom client machines can provide effective load balancing, but clientcooperation is not strictly needed.

Embodiments of the invention include a distributed file server (orservers) comprising a number of hardware resources, includingcontrollers, storage elements such as disks, network elements, and thelike. Multiple client machines can be connected through a client networkor communication fabric to one or more server clusters, each of whichincludes of one or more controllers and a disk storage pool.

File system software resident on each controller can collect statisticsregarding file accesses and server resource utilization. This includesinformation of the access frequency, access bandwidth and accesslocality for the individual objects stored in the distributed file, theloading of each controller and disk storage element in terms of CPUutilization, data transfer bandwidth, and transactions per second, andthe loading of each network element in terms of network latency and datatransfer bandwidth.

The collected statistics can be subjected to various filter operations,which can result in a prediction of future file and resource utilization(i.e. workload). The prediction can also be modified by serverconfiguration data which has been provided in advance, for example, by asystem administrator, and explicit indications regarding future fileand/or resource usage which may be provided directly from a clientmachine.

The predicted workload can then be used to move content (files, objects,or the like) between storage elements and to direct client accesses tocontrollers in such a manner that the overall workload is distributed asevenly as possible, resulting in best overall load balance across thedistributed file storage system and the best system performance.

The predicted workload can be employed to perform client network loadbalancing, intra-cluster storage load balancing, inter-node storage loadbalancing, intra-node storage capacity balancing, inter-node storagecapacity balancing, file replication load balancing, or the like.

Client network load balancing includes managing client requests to theextent possible such that the client load presented to the severalcontrollers comprising a server cluster, and the load presented to theseveral client network ports within each is evenly balanced.Intra-cluster storage load balancing includes the movement of databetween the disks connected to a controller cluster such that the diskbandwidth loading among each of the drives in an array, and the networkbandwidth among network connecting disk arrays to controllers isbalanced. For example, intra-cluster storage load balancing can beaccomplished by moving relatively infrequently accessed files orobjects. Intra-cluster storage load balancing advantageously achievesuniform bandwidth load for each storage sub-network, while alsoachieving uniform bandwidth loading for each individual disk drive.

Inter-node storage load balancing comprises the movement of data betweendrives connected to different controller clusters to equalize diskaccess load between controllers. This can often cost more thanintra-node drive load balancing, as file data is actually copied betweencontrollers over the client network. Intra-node storage capacitybalancing comprises movement of data between the disks connected to acontroller (or controller pair) to balance disk storage utilizationamong each of the drives.

Inter-node storage capacity balancing comprises movement of data betweendrives connected to different controllers to equalize overall diskstorage utilization among the different controllers. This can often costmore than intra-node drive capacity balancing, as file data is actuallybe copied between controllers over the network. File replication loadbalancing comprises load balancing through file replication as anextension of inter-node drive load balancing. For example, high usagefiles are replicated so that multiple controller clusters include one ormore that one local (read only) copy. This allows the workloadassociated with these heavily accessed files to be distributed across alarger set of disks and controllers.

Based on the foregoing, embodiments of the present invention include adistributed file storage system that proactively positions objects tobalance resource loading across the same. As used herein, load balancingcan include, among other things, capacity balancing, throughputbalancing, or both. Capacity balancing seeks balance in storage, such asthe number of objects, the number of Megabytes, or the like, stored onparticular resources within the distributed file storage system.Throughput balancing seeks balance in the number of transactionsprocessed, such as, the number of transactions per second, the number ofMegabytes per second, or the like, handled by particular resourceswithin the distributed file storage system. According to one embodiment,the distributed file storage system can position objects to balancecapacity, throughput, or both, between objects on a resource, betweenresources, between the servers of a cluster of resources, between theservers of other clusters of resources, or the like.

The distributed file storage system can proactively position objects forinitial load balancing, for example, to determine where to place aparticular new object. While existing server loading is a factor used inthe determination, other data can be used to help predict the accessfrequency of the new object, such as, for example, file extensions, DVaccess attributes, or the like. For example, a file extension indicatinga streaming media file can be used to predict a likely sequential accessto the same.

The distributed file storage system actively continues load balancingfor the existing objects throughout the system using load balancingdata. For capacity load balancing, large objects predicted to beinfrequently accessed, can be moved to servers, which for example, havethe lower total percent capacity utilizations. Movement of such filesadvantageously avoids disrupting throughput balancing by movingpredominantly infrequently accessed files. For throughput balancing,objects predicted to be frequently accessed can be moved to servers,which for example, have the lower total percent transactionutilizations. In one embodiment, smaller objects predicted to befrequently accessed can be moved in favor of larger objects predicted tobe frequently accessed, thereby advantageously avoiding the disruptionof capacity balancing.

According to one embodiment, one or more filters may be applied duringinitial and/or active load balancing to ensure one or a small set ofobjects are not frequently transferred, or churned, throughout theresources of the system.

The distributed file storage system can comprise resources, such as aserver or server, which can seek to balance the loading across thesystem by reviewing a collection of load balancing data from itself, oneor more of the other servers in the system, or the like. The loadbalancing data can include object file statistics, server profiles,predicted file accesses, historical statistics, object patterns, or thelike. A proactive object positioner associated with a particular servercan use the load balancing data to generate an object positioning plandesigned to move objects, replicate objects, or both, across otherresources in the system. Then, using the object positioning plan, theresource or other resources within the distributed file storage systemcan execute the plan in an efficient manner.

According to one embodiment, the generation of the positioning plan canbe very straightforward, such as, for example, based on object sizes andhistorical file access frequencies. Alternatively, the generation of theplan can be quite complex, based on a large variety of load balancinginformation applied to predictive filtering algorithms, the output ofwhich is a generally more accurate estimate of future file accesses andresource usage, which results in more effective object positioning.Another embodiment can include adaptive algorithms which track theaccuracy of their predictions, using the feedback to tune the algorithmsto more accurately predict future object access frequencies, therebygenerating effective object positioning plans.

According to one embodiment, each server pushes objects defined by thatserver's respective portion of the object positioning plan to the otherservers in the distributed file storage system. By employing the serversto individually push objects based on the results of their objectpositioning plan, the distributed file storage system provides aserver-, process-, and administrator-independent automated approach toobject positioning, and thus load balancing, within the distributed filestorage system.

To facilitate a complete understanding of exemplary load balancingaspects of the invention, this part of the detailed descriptiondescribes the invention with reference to FIGS. 39-41, wherein likeelements are referenced with like numerals throughout.

FIG. 39 depicts an exemplary embodiment of servers and disk arrays of adistributed file storage system (DFSS) 3900, disclosed for the purposeof highlighting the distributed proactive object positioning aspects ofan exemplary embodiment of the invention. A skilled artisan willrecognize FIG. 39 is not intended to limit the large number of potentialconfigurations of servers and disk arrays encompassed by the foregoingdistributed file storage system 100 disclosed with reference to FIG. 1.As shown in FIG. 39, the DFSS 3900 comprises five nodes formed intothree clusters 3905, 3910, and 3915. Cluster 3905 includes a first nodecomprising server F1 and a disk array 3920, and a second node comprisingserver F2 and a disk array 3922. Cluster 3910 includes one nodecomprising server F3 and a disk array 3924. Additionally, cluster 3915includes a first node comprising server F4 and a disk array 3926, and asecond node comprising server F5 and a disk array 3928.

According to one embodiment, each of the servers F1, F2, F3, F4, and F5comprises software, hardware, and communications similar to the servers130-135 disclosed with reference to FIGS. 1 and 2. For example, serverF1 communicates with each drive of the disk array 3920. Additionally,server F1 forms part of cluster 3905. According to one embodiment, atleast some of the objects stored on a disk array within a cluster, arestored, and are thereby accessible, on other disk arrays within thecluster. For example, server F1 can be configured to communicate witheach drive of the disk array 3922. Server F1 also communicates with oneor more of the other servers of the DFSS 3900. Moreover, the servers F1,F2, F3, F4, and F5 include software and hardware systems which employsome or all of the features of the distributed file storage system 100,such as, for example, the disclosed use of metadata structures forobject organization, metadata and data caching, and the like.

FIG. 39 also shows exemplary self-explanatory attributes of each of thedrives of the disk arrays 3920-3928. For example, the drives of the diskarray 3920 include two high speed drives having small storage capacity,e.g., “FAST, SMALL,” one drive having high speed and average storagecapacity, e.g., “FAST, AVERAGE,” and one drive having average speed andlarge storage capacity, e.g., “AVERAGE, LARGE.” Additionally, FIG. 39shows servers F3 and F4 providing access to a resource, such as, forexample, a printer, scanner, display, memory, or the like. A skilledartisan will recognize from the disclosure herein that the speed of adrive includes its ordinary meaning as well as a measure of the datarate, or the like, of read or write operations.

According to one embodiment, the DFSS 3900 includes proactive objectpositioning. For example, each server F1-F5 of the DFSS 3900 proactivelypositions objects, such as files, directories, or the like, based on adesire to balance or optimize throughput, capacity, or both. Accordingto one embodiment, the foregoing balancing and optimization canadvantageously occur at multiple levels within the DFSS 3900. Forexample, the DFSS 3900 can advantageously seek to optimize the placementand structure of objects within and between disks of the disk arrays,between the servers of a cluster and between servers of other clusters.

Load Balancing Within and Between the Drives of the Disk Arrays

Similar to the embodiments disclosed with reference to FIGS. 1 and 5,the DFSS 3900 provides the server F1 with the ability to adjust the filelogical block size and the distribution of files across multiple drivesusing, for example, the Gee Table 320. Thus, the server F1 can adjust orchoose the layout of particular files within a disk, using, for example,larger file logical block sizes for larger files, or the like, therebycreating efficient storage of the same. Moreover, the server F1 canadjust or choose the layout of particular files across varying numbersof disks, thereby matching, for example, performance of drives withinthe disk array 3920 with attributes of particular files.

For example, FIG. 39 shows the placement of two files within the DFSS3900, e.g., streamed file “SF” and large file “LF.” According to theexemplary embodiment, file “SF” comprises a file which is to be streamedacross computer networks, such as, for example, the Internet. As shownin FIG. 39, file SF is stored in the disk array 3920 using a distributedparity group of three blocks, e.g., two data blocks, “SF₁,” and “SF₂,”and one parity block “SF₃.” Similar to the foregoing description ofdistributed file storage system 100, the DFSS 3900 advantageously allowsfiles to modify the number of drives in the distributed parity group fora variety of reasons, including to take advantage of attributes of adisk array. Thus, when it is determined that it is desirable to storefile SF on only fast disk drives, the distributed parity group can bechosen such that file SF is stored on the fastest drives of disk array3920 in equally shared portions. A skilled artisan will recognize fromthe disclosure herein that the servers advantageously balance the desireto employ the faster drives of a particular disk array, against thedesire to reduce the overhead associated with using smaller paritygroups. For example, according to some embodiments, use of only twodisks of five disks means that half of the data stored is overheadparity data.

FIG. 39 also shows that in the disk array 3922, file SF′, a copy of fileSF, can be stored according to the attributes of the disk array 3922,e.g., file SF′ is stored using a distributed parity group of two becausethe disk array 3922 has only two fast drives. Moreover, FIG. 39 showsfile LF stored in the disk array 3924. According to the exemplaryembodiment, file LF is stored is using distributed parity groups ofthree blocks, thereby fully taking advantage of all three very fastdrives.

Thus, the server F1 advantageously and proactively can adjust theplacement and structure of objects, such as files, within and betweendrives of the disk array 3920. A skilled artisan will recognize thatsuch proactive placement is outside the ability of conventional datastorage systems. For example, as disclosed with reference to FIGS.14-16, the DFSS 3900 advantageously includes a directory and file handlelookup process which allows the clients 110 to find files without firstknowing which server is currently storing the file. Thus, when one ofthe servers of the DFSS 3900 repositions an object to balance load,capacity, or the like, the clients 110 can use the lookup process tofind the repositioned object in its new location.

Load Balancing Between Servers of a Cluster

As disclosed in the foregoing, one embodiment of the DFSS 3900 seeks tobalance the loading and capacity between servers of a cluster. Asdisclosed with reference to the embodiments of FIGS. 1 and 13-14, theclients 110 request data from a file through the use of the file handle1300, which according to one embodiment, includes the serveridentification 1320. Thus, the DFSS 3900 can advantageously alter theserver identification 1320 of the file handle 1300 for a particularfile, thereby changing the read or write request from being processedby, for example, server F1 to, for example, server F2. A skilled artisanwill recognize a wide number of reasons for making the foregoingalteration of the file handle 1300, including the availability of F1,the load of F1 versus F2, or the like. In addition, the DFSS 3900 canalter the file handle 1300 based on comparisons of server load balancingdata, to set up read-only copies of heavily accessed files, or the like,as discussed below.

Load Balancing Between Servers of Other Clusters

Load balancing between servers differs from load balancing betweendrives in, among other things, load balancing between servers involvesbalancing through the movement or creation of additional copies ofobjects, while load balancing between drives involves the movement ofdata blocks.

One embodiment of the DFSS 3900 comprises servers F1-F5 each havingaccess to load balancing data from itself and each of the other servers.According to one embodiment, each server uses the load balancing data togenerate an object positioning plan, and then pushes objects defined bytheir respective portion of the plan, to other servers in the DFSS 3900.The foregoing implementation provides a distributed andserver-independent approach to object positioning within the DFSS 3900.It will be understood by a skilled artisan from the disclosure hereinthat resources, or groups of resources, can gather load balancing data,such as, for example, each, some, or all clusters, each, some, or allservers, or the like.

According to one embodiment, the load balancing data of a particularserver can include a wide variety of statistical and attribute datarelating to the architecture and performance of the respective serverand disk array. Additional statistical information can be maintainedrelating to the historical object access frequencies and patterns. Thisstatistical information can be applied to a filtering function topredict future object frequencies and patterns.

The load balancing data can include relatively static information, suchas, for example, the number of servers for a given cluster and thenumber of drives connected to each server. Moreover, for each server,the load balancing data can include an indication of the number and typeof interfaces available to the server, performance statistics of theserver, amount of available memory, an indication of the health of theserver, or the like. For each drive, the load balancing data can includean indication of the layout of the drive, such as track information,cylinder information, or the like, capacity and performance information,performance statistics, an indication of the health of the drive, or thelike. Additionally, the load balancing data can include an indication ofthe performance and the health of storage network configurations, clientnetwork configurations, or the like. The relatively static loadbalancing data can be considered the “profile” of the resourcesassociated therewith.

Other relatively static information can include an indication of thequality of service being demanded by the clients 110 from a particularserver, such as, for example, server F1 and its associated disk array3920 can be configured to provide data availability with little or nodowntime, thereby allowing the server to support Internet hostingapplications or the like. Additionally, the foregoing relatively staticstatistical or attribute information can change occasionally, such as,for example, when a drive is replaced or added, a server isreconfigured, the quality of service is changed, or the like.

According to yet another embodiment, the load balancing data can alsoinclude relatively dynamic information, such as, for example, throughputinformation like the number of read or write input/output operations persecond (IOPS). For example, the dynamic information can include serverthroughput for each server, such as, for example, client transactionsper second, client megabytes per second, disk transaction per second,disk megabytes per second, or the like. The foregoing server throughputinformation can include read, write, or both operations for each clientinterface of the particular server. The server throughput data alsoincludes dynamic information such as the cache hit ration, errors, orthe like, of each particular server. The dynamic information can alsoinclude disk throughput for each disk, such as, for example, anindication of the amount of metadata capacity that is being utilized,the amount of data capacity utilized, read, write, or both transactionsper second, read, write, or both megabytes per second, errors or thelike.

In addition to the foregoing data, the load balancing data includesobject statistic information, such as, for example, the last access timeand the access frequency for each object. According to one embodiment,the measurement of access frequency can be filtered using one or morefiltering weights designed to emphasize, for example, more recent dataover more historical data.

According to one embodiment, each server may include file statisticalinformation in the load balancing data, comprising additionalinformation for the more heavily accessed, and potentially smaller,objects. For example, the file statistical information can include anindication of access frequency for, for example, the last ten (10)minutes, one (1) hour, twenty-four (24) hours, or the like. Moreover,the file statistical information can include average read block size,average write block size, access locality, such as a indication ofrandomness or sequentialness for a given file, histogram data ofaccesses versus day and time, or the like. According to one embodiment,the indication of randomness can include randomness rating, such as, forexample, a range from 0 and 1, where 0 corresponds to primarily randomlyaccessed file and one corresponds to a primarily sequentially accessedfile, or vice versa.

Based on the above, the load balancing data for a given server caninclude virtually any information, performance or attribute statistic,or the like that provides insight into how objects, such as files anddirectories, should be created, reconfigure, moved, or the like, withinthe DFSS 3900. For example, a skilled artisan can include additionalinformation useful in the prediction of file access frequencies, suchas, for example, the time of day, the file size, the file extension, orthe like. Moreover, the additional information can include hintscorresponding to dynamic volume access attributes, such as, for example,block size, read/write information, the foregoing quality of serviceguarantees or the randomness/sequentialness of file access.

According to one embodiment, the load balancing data can include a LeastRecently Used (LRU) stack and/or a Most Recently Used (MRU) stack,advantageously providing insight into which objects can be used forbalancing capacity, throughput, or both, within the DFSS 3900. Forexample, according to one embodiment, the LRU stack tracks the objectsthat are rarely or infrequently accessed, thereby providing informationto the servers about which objects can be mostly ignored for purposes ofthroughput balancing, and are likely candidates for capacity balancing.The MRU stack tracks the objects that are more frequently accessed,thereby providing information to the servers about which objects arehighly relevant for throughput balancing. According to one embodiment,the servers F1-F5 can employ the MRU stack to determine the objects, onwhich the servers should be tracking additional performance statisticsused in more sophisticated load balancing or sharing solutions, asdiscussed in the foregoing.

A skilled artisan will recognize from the disclosure herein that the MRUand LRU stacks can be combined into a single stack or other structuretracking the frequency of access for some or all of the objects of theservers F1-F5. A skilled artisan will also recognize from the disclosureherein that the time frame chosen for determining frequency of use for agiven object affects the throughput and capacity balancing operations.For example, if the time frame is every twelve hours, the number ofobjects considered to be frequently accessed may be increased ascompared to a time frame of every half-second. According to oneembodiment, the DFSS 3900 uses an adaptive time frame often (10) minutesto twenty-four (24) hours.

Although the load balancing data is disclosed with reference to itspreferred embodiment, the invention is not intended to be limitedthereby. Rather, a skilled artisan will recognize from the disclosureherein a wide number of alternatives for the same. For example, the loadbalancing data can include detailed performance statistics similar tothose disclosed above. On the other hand, the load balancing data caninclude only a few data points providing only a rough sketch of thethroughput and capacity on a particular server. Moreover, the server maytrack access frequency using information contained in the G-Node of anobject, such as, for example, the last access time, or “atime,” field.

FIG. 40 illustrates a block diagram of an exemplary server 4000, such asthe servers F1-F5 of FIG. 39, according to aspects of an exemplaryembodiment of the invention. As shown in FIG. 40, the server 4000include a server interface 4005, a server software or file system 4010,load balancing data 4020, and an object positioning plan 4025. Theserver interface 4005 passes data access requests from, for example, theclients 110, to the file system 4010. The server interface 4005 includesa server manager 4008, which collects client access statistics, such astransactions per second per client, per port, and per server, andmegabytes per second per client, per port, and per server. The serversystem 4010 includes several layers that participate in statisticscollection. For example, the server system 4010 includes a requestprocessing layer 4012, a data/metadata management layer 4014, and astorage management layer 4016. The request processing layer 4012collects the statistics related to accesses to specific files. Thedata/metadata management layer 4014 collects drive resource and capacityutilization information. The storage management layer 4016 collectsstatistics related to transactions per second and megabytes per secondfor each storage network interface and drive.

FIG. 40 also shows that each server 4000, such as the servers F1-F5 ofFIG. 39, includes a proactive object positioner 4018, according toaspects of an exemplary embodiment of the invention. According to oneembodiment, the positioner 4018 comprises a set of rules, a softwareengine, or the like, employing logic algorithms to some or all of theload balancing data 4020 to generate the object positioning plan 4025.

As disclosed in the foregoing, the servers F1, F2, F3, F4, and F5, eachshare their respective load balancing data with one another. Thus, theload balancing data 4020 comprises load balancing data from theparticular server, in this example, server F3, and the load balancingdata from each of the other servers, F1-F2 and F4-F5. According to oneembodiment, a server transmits its load balancing data at predeterminedtime intervals. According to another embodiment, each server determineswhen a significant change or a time limit has expired since the lastbroadcast of its load balancing data, and then broadcasts the same.

As shown in FIG. 40, each server 4000 includes the proactive objectpositioner 4018, which accepts as an input, the load balancing data ofthe some or all of the servers, and generates as an output, the objectpositioning plan 4025. According to one embodiment, the proactive objectpositioner 4018 for a given server generates a plan for that server. Theserver then attempts to push objects found in the plan to the otherservers in the DFSS 3900 to balance throughput, capacity, or both.According to another embodiment, the proactive object positioner 4018for a given server generates the plan 4025, which is relevant to allservers. In such a case, the server attempts to push only its objectsfrom the plan 4025 to other servers. Thus, each server in the DFSS 3900acts independently to accomplish the plan 4025 of the entire DFSS 3900,thereby advantageously providing a distributed and balanced approachthat has no single point of failure and needing, if any, only minimalsupervision.

As discussed in the foregoing, the object positioner 4018 correspondingto each server in the DFSS 3900 can generate the positioning plan 4025to position objects to balance capacity, throughput, or both.

Positioning to Balance Capacity, Such as the Number or Size of Objects

According to one embodiment, the proactive object positioner 4018 foreach server can instruct its server to balance the number of objectsstored on some or each disk array of the DFSS 3900. For example, asdisclosed with reference to FIG. 5, each server has a predefined amountof memory for caching the G-nodes of the objects stored on the diskarray associated with that server. By balancing the number of objectsrelated to a particular server, the DFSS 3900 advantageously avoidshaving more G-node data for a server than can be stored in that server'sG-node memory cache.

According to one embodiment, the proactive object positioner 4018 foreach server can instruct its server to balance the size of objectsstored on some or each disk array of the DFSS 3900. For example, if aparticular server is associated with a disk array having a large numberof small objects stored therein, the server can exceed that server'sG-node memory cache. Therefore, each proactive object positioner 4018can instruct its server to push objects such that the size of objectsaccessible by each server is balanced. For example, the servers canevenly distribute the number of small objects, the number ofmedium-sized objects, and the number of large objects between servers.By balancing the size of objects related to a particular server, theDFSS 3900 reduces the chances of having more G-node data for a serverthan can be stored in that server's G-node memory cache.

According to yet another embodiment, the proactive object positioner4018 for each server can instruct its server to optimize the number offree and used data blocks when the servers in the DFSS 3900 have a largeaverage object size. In such case, the number of G-nodes and the G-nodememory cache will not likely be a performance issue, although number ofused versus free data blocks will likely be an issue. While used versusfree data blocks need not be entirely uniform across servers,maintaining a certain level of unused block capacity for each serverprovides flexibility in throughput balancing and new object creation,thereby enhancing the performance of the overall DFSS 3900.

Positioning to Balance Throughput, Such as the Access Frequency ofObjects

According to one embodiment, the proactive object positioner 4018generates the positioning plan 4025 to position objects based on, forexample, predicted access frequencies of the same. As discussed above,prediction may comprise historical data, and may comprise a number ofother data and factors as well. The positioner 4018 can advantageouslyuse objects predicted to be infrequently accessed for capacity balancingto avoid upsetting any throughput balancing already in place. Forexample, when the positioner 4018 determines to balance the capacityamong resources of the DFSS 3900, such as, for example, a drive, diskarray, or server, the positioner 4018 can move objects that are oflittle significance to the throughput of the resource, such as, forexample, those objects predicted to be least accessed. Thus, as thepositioner 4018 balances the capacity through objects predicted to be,or found to be least recently accessed, the respective throughput of theresources will not be substantially affected. According to oneembodiment, each server tracks the objects predicted to be infrequentlyused by maintaining in their load balancing data, an LRU stack of, forexample, pointers to the G-Nodes of the objects predicted to beinfrequently accessed.

Additionally, the positioner 4018 can generate the positioning plan 4025to move objects predicted to be infrequently accessed from faster drivesto slower drives. For example, if the large file LF from FIG. 39 werepredicted to be infrequently accessed, storage of file LF on the fastestdrives of the DFSS 3900, for example, the drives of the disk array 3924,would be inefficient. Thus, the proactive object positioner 4018determines that the large file LF predicted to be infrequently accessedcan be advantageously stored on the slow, large drives of the disk array3926 of server F4. A skilled artisan will recognize that movement of thefile LF to servers F4 is not expected to substantially affect thethroughput of servers F3 and F4, outside of the processes for moving thefile LF.

Additionally, the proactive object positioner 4018 can use the MRU stackin a server's load balancing data to instruct an overburdened server totake actions to offload some of the access from itself to those serverswith less throughput. For example, the positioner 4018 can generateinstructions to move the objects predicted to be heavily accessed toother servers, thereby moving the entire throughput load associatedtherewith, to the other servers. Also, positioner 4018 can generateinstructions to create copies of objects predicted to be heavilyaccessed on other servers, thereby sharing the throughput load with theother servers

For example, according to one embodiment, the server F1 includes thestreamed file SF predicted to be heavily accessed, which in this examplemay include extremely popular multimedia data, such as, for example, anew video or music release, a major news story, or the like, where manyclients are requesting access of the same. Moreover, according to thisembodiment, the server F1 is being over-utilized, while the server F3 isbeing under-utilized. Thus, the object positioner 4018 recognizes thatthe movement of the file SF to the server F3 may simply overload theserver F3. According to one embodiment, the proactive object positioner4018 can instruct the server F1 to push, for example, read-only copiesof the file SF to the server F3. Moreover, a skilled artisan willrecognize from the disclosure herein that the server F1 can then returnto a requesting client, a file handle 1300 for the file SF designatingserver F3, and the client will then generate requests to server F3,instead of server F1. Accordingly, the over utilization of server F1 isadvantageously decreased while the under utilization of server F3 isadvantageously increased, thereby balancing the throughput across theDFSS 3900.

According to yet another embodiment, the proactive object positioner4018 can generate instructions to move objects to match the attributesof resources available to a particular server, thereby potentiallydecreasing the response time of the DFSS 3900. For example, asillustrated in the foregoing embodiment, the object positioner 4018 caninstruct the server F1 to push the file SF predicted to be heavilyaccessed, to the server F3 having very fast disk drives, even when theserver F1 is not being over-utilized. Moreover, as discussed above, thepositioner 4018 can instruct the server F3 to store the file indistributed parity groups matching the number of very fast drives.

According to one embodiment, one or more of the servers can includespecific software and hardware solutions, such as dedicated digitalsignal processors, which can add additional horse power to thegeneration of the object positioning plan 4025. For example, loadbalancing can be performed by an external client connected to the DFSS3900.

FIG. 41 depicts the object positioning plan 4025 of server F3 of FIG.39, according to aspects of an exemplary embodiment of the invention. Asshown in FIG. 41, the plan 4025 includes instructions to push an object,and instructions on how to handle subsequent client requests for accessto that object. According to one embodiment, a server that pushes anobject tells clients seeking access to the object that the object hasbeen moved. The pushing server can maintain a cache of objects that itrecently pushed, and when feasible, the pushing server will supply therequesting client with the location, or server, where the object wasmoved, thereby providing direct access to the object for the client.

As shown in FIG. 41, the plan 4025 calls for server F3 to push the largefile LF to server F4 for storage thereon, thereby freeing the fastestdrives in the DFSS 3900 to store more objects predicted to be moreheavily accessed. Moreover, the plan 4025 includes an indication thatserver F3 will return an indication of staleness for any clients stillcaching the file handle of file LF designating server F3. The plan 4025also indicates that if server F1 requests, server F3 will accept andstore a copy of the streamed file SF and return an indication of filecreation to server F1, such as, for example, the file handle of serverF3's copy of file SF. Thus, the DFSS 3900 uses a pushing approach toensure server independence in proactively placing objects.

Based on the foregoing disclosure related to FIGS. 39-41, a skilledartisan will recognize the vast scalability of the DFSS 3900. Forexample, adding or removing hardware components such as drives,resources, or even servers, simply causes updated, or sometimesadditional, load balancing information to be broadcast to the otherservers. Each server then can immediately generate new positioning plansto take full advantage of the new components or configuration of theDFSS 3900. Each server then pushes their respective objects throughoutthe DFSS 3900, thereby efficiently balancing the throughput, capacity,or both, of the same.

Although the foregoing invention has been described in terms of certainpreferred embodiments, other embodiments will be apparent to those ofordinary skill in the art from the disclosure herein. For example, theDFSS 3900 may advantageously push new file handles to clients, such as,for example, file handles including information on the location of anobject. According to another embodiment, the DFSS 3900 canadvantageously allow servers who have pushed objects to other servers,to automatically suggest new file handles to requesting clients.However, this approach can have the drawback that the file handle storedby the old server can itself be outdated, for example, when the newserver subsequently pushed the same object to yet another server. Thus,according to one embodiment, servers return indications of staleness forobjects they not longer have stored on their respective disk arrays.

In addition, a skilled artisan will recognize from the disclosure hereinthat many of the balancing ideas can be implemented in conventionalnon-distributed file storage systems. For example, the method of movinginfrequently accessed files to balance capacity so as not to upsetbalanced load can be incorporated into conventional data storagesystems.

Data Flow Architecture

Each server 130-135 in the DFSS 100 includes storage controller hardwareand storage controller software to manage an array of disk drives. Forexample, the servers 130-131 each manage data on the disk arrays 140 and141. A large number of disk drives can be used, and the DFSS 100 can beaccessed by a large number of client machines 110. This potentiallyplaces a large workload on the servers 130-135. It is thereforedesirable that the servers 130-135 operate in an efficient manner toreduce the occurrence of bottlenecks in the storage system.

Prior art approaches for storage servers tend to be software intensive.Specifically, a programmable CPU in the server becomes involved in themovement of data between the client and the disks in the disk array.This limits the performance of the storage system because the server CPUbecomes a bottleneck. While prior approaches may have a certain degreeof hardware acceleration, such as XOR parity operations associated withRAID, these minimal acceleration techniques do not adequately offloadthe server CPU.

FIG. 42 shows an architecture for a server, such as the server 130, thatreduces loading on a CPU 4205 of the server 130. As shown in FIG. 42,the clients 110 communicate (over the network fabric 120, not shown)with one or more network interfaces 4214. The network interfaces 4214communicate with a first I/O bus 4201 shown as a network bus. Thenetwork bus communicates with the CPU 4205 and with a data engine 4210.A first data cache 4218 and a second data cache 4220 are provided to thedata engine 4210. A metadata cache 4216 is provided to the CPU 4205. TheCPU 4205 and the data engine 4210 also communicate with a second I/O bus4202 shown as a storage bus. One or more storage interfaces 4212 alsocommunicate with the second bus 4202.

The storage interfaces 4212 communicate with the disks 140, 141. In oneembodiment, the first I/O bus 4201 is a PCI bus. In one embodiment, thesecond I/O bus 4202 is a PCI bus. In one embodiment, the caches 4216,4218, and 4220 are non-volatile. In one embodiment, the networkinterfaces 4214 are Fibre Channel interfaces. In one embodiment, thestorage interfaces 4212 are Fibre Channel interfaces. The data engine4210 can be a general-purpose processor, a digital signal processor, aField Programmable Gate Array (FPGA), other forms of soft or hardprogrammable logic, a custom ASIC, etc. The network interfacecontrollers 4214, 4212 can support Fibre Channel, Ethernet, Infiniband,or other high performance networking protocols.

The architecture shown in FIG. 42 allows data to be efficiently movedbetween the client machines 110 and disks 140-141 with little or nosoftware intervention by the CPU 4205. The architecture shown in FIG. 42separates the data path from the control message path. The CPU 4205handles control, file system metadata, and housekeeping functions(conceptually, the CPU 4205 can be considered as a control engine).Actual file data passes through the data engine 4210.

Control messages (e.g. file read/write commands from clients) are routedto the CPU 4205. The CPU 4205 processes the commands, and queues datatransfer operations to the data engine 4210. The data transferoperations, once scheduled with the data engine 4210 can be completedwithout further involvement of the CPU 4205. Data passing between thedisks 140, 141 and the clients 110 (either as read or write operations)is buffered through the data cache 4218 and/or the data cache 4220. Inone embodiment, the data engine 4210 operates using a data flowarchitecture that packages instructions with data as the data flowsthrough the data engine 4210 and its associated data caches.

The data engine 4210 provides a separate path for data flow byconnecting the network interfaces 4214 and the storage interfaces 4212with the data caches 4218, 4220. The data engine 4210 provides file datatransfers between the network interface 4214 and the caches 4218, 4220and between the storage interface 4212 and the caches 4218, 4220. As anexample of the data path operation, consider a client file readoperation. A client read request is received on one of the networkinterfaces 4214 and is routed to the CPU 4205. The CPU 4205 validatesthe request, and determines from the request which data is desired. Therequest will typically specify a file to be read, and the particularsection of data within the file. The CPU 4205 will use file metadata inthe cache 4216 to determine if the data is already present in one of thedata caches 4218, 4220, or if the data must be retrieved from the disks140, 141. If the data is in the data cache 4218, 4220, the CPU 4205 willqueue a transfer with the network interfaces 4214 to transfer the datadirectly from the appropriate data cache 4218, 4220 to the requestingclient 110, with no further intervention by the CPU 4205. If the data isnot in the data caches 4218, 4220, then the CPU 4205 will queue one ormore transfers with the storage interfaces 4212 to move the data fromthe disks 140, 141 to the data caches 4218, 4220, again without furtherintervention by the CPU 4205. When the data is in the data caches 4218,4220, the CPU 4205 will queue a transfer on the network interfaces 4214to move the data to the requesting client 110, again without furtherintervention by the CPU 4205.

One aspect of the operation of the data engine 4210 is that the CPU 4205schedules data movement operations by writing an entry onto a queue inthe network interfaces 4214 or into a queue in the storage interfaces4212. The data engine 4210 and the network and storage interfaces 4214,4212 are connected by busses 4201, 4202. The busses 4201, 4202 eachinclude an address bus and a data bus. In one embodiment, the network orstorage interfaces 4214, 4212 perform the actual data movement (orsequence of data movements) independently of the CPU 4205 by encoding aninstruction code in the address bus that connects the data engine to theinterface. The instruction code is set up by the host CPU 4205 when thetransfer is queued, and can specify that data is to be written or readto one or both of the cache memories 4218, 4220. In addition, theinstruction code can specify that an operation such as a parity XORoperation or a data conversion operation be performed on the data whileit is in transit through the data engine 4210. Because instructions arequeued with the data transfers, the host CPU can queue hundreds orthousands of instructions in advance with each interface 4214, 4212, andall of these instructions can be can be completed asynchronously andautonomously.

As described above, once a data movement operation has been queued, thedata engine 4210 offloads the CPU 4205 from direct involvement in theactual movement of data from the clients 110 to the disks 140, 141, andvice-versa. The CPU 4205 schedules network transfers by queuing datatransfer operations on the network interfaces 4214 and the storageinterfaces 4212. The interfaces 4214 and 4212 then communicate directlywith the data engine 4210 to perform the data transfer operations. Somedata transfer operations involve the movement of data. Other datatransfer operations combine the movement of data with other operationsthat are to be performed on the data in transit (e.g., paritygeneration, data recovery, data conversion, etc.). The processingmodules in the data engine 4210 can perform five principal operations,as well as a variety of support operations. The principal operationsare:

-   -   1) read from cache    -   2) write to cache    -   3) XOR write to cache    -   4) write to one cache with XOR write to other cache    -   5) write to both caches

A typical client file read operation would proceed as follows in theserver 130:

-   -   (1) The file read command is received from the client    -   (2) The CPU 4205 authenticates client access and access        permissions. The CPU 4205 also does metadata lookups to locate        the requested data in cache or on disk.    -   (3) If data is not in cache, a disk read transaction is queued        by sending instructions to the storage interfaces 4212.    -   (4) The storage interfaces 4212 mode data from disk to the data        caches 4218, 4220.    -   (5) The CPU 4205 queue a data-send transaction to the network        interfaces 4214.    -   (6) The network interfaces 4214 send the data to the client,        completing the client read operation.

FIG. 43 is a block diagram of the internal structure of an ASIC 4310that is one example of a hardware embodiment of the data engine 4210.The ASIC 4310 provides the capability for autonomous movement of databetween the network interfaces 4214 and data caches 4218, 4220, andbetween the storage interfaces 4212 and the data caches 4218, 4220. Theinvolvement of the CPU 4205 is often just queuing the desired transferoperations. The ASIC 4310 supports this autonomy by combining anasynchronous data flow architecture, a high-performance data path thancan operate independently of the data paths of the CPU 4205, and a datacache memory subsystem. The ASIC 4310 also implements the paritygeneration functions used to support a RAID-style data protectionscheme.

The data ASIC 4310 is a special-purpose parallel processing system thatis data-flow driven. That is, the instructions for the parallelprocessing elements are embedded in data packets that are fed to theASIC 4310 and to the various functional blocks within the ASIC 4310.

In one embodiment, the ASIC 4310 has four principal interfaces: a firstdata cache interface 4318, a second data cache interface 4320, a firstbus interface 4301, and a second bus interface 4302. Other versions ofthe ASIC 4310 can have a different number of interfaces depending onperformance goals.

Data from the first data cache interface 4318 is provided to a cacheread buffer 4330, to a feedback buffer 4338, to a feedback buffer 4340and to a cache read buffer 4348. Data from the second data cacheinterface 4320 is provided to a cache read buffer 4331, to a feedbackbuffer 4339, to a feedback buffer 4341 and to a cache read buffer 4349.

Data is provided from the bus interface 4301 through a write buffer 4336to a parity engine 4334. Data is provided from the parity engine 4334through a cache write buffer 4332 to the cache interface 4318. Data isprovided from the feedback buffer 4338 to the parity engine 4334.

Data is provided from the bus interface 4302 through a write buffer 4346to a parity engine 4344.

Data is provided from the parity engine 4344 through a cache writebuffer 4342 to the cache interface 4318. Data is provided from thefeedback buffer 4340 to the parity engine 4344.

Data is provided from the bus interface 4301 through a write buffer 4337to a parity engine 4335. Data is provided from the parity engine 4335through a cache write buffer 4333 to the cache interface 4320. Data isprovided from the feedback buffer 4339 to the parity engine 4335.

Data is provided from the bus interface 4302 through a write buffer 4347to a parity engine 4345. Data is provided from the parity engine 4345through a cache write buffer 4343 to the cache interface 4320. Data isprovided from the feedback buffer 4341 to the parity engine 4345.

Data is provided from the cache read buffers 4348, 4349 to the businterface 4202. Data is provided from the cache read buffers 4330, 4331to the bus interface 4201.

Data transfer paths are provided between the cache interface 4218 andthe bus interface 4301 and 4302. Similarly, data transfer paths areprovided between the cache interface 4220 and the bus interfaces 4301and 4302. A control logic 4380 includes, in each of these data path, aprocessing engine that controls data movement between the respectiveinterfaces as well as operations that can be performed on the data as itmoves between the interfaces. The control logic 4380 is data-flow drivenas described above.

In one embodiment, the bus 4201 is a PCI bus, the bus 4202 is a PCI bus,and data-transfer commands for the data engine are contained in PCIaddresses on the respective buses. FIG. 44 is a map 4400 of data fieldsin a 64-bit data transfer instruction to the data engine for use with a64-bit PCI bus. A cache address is coded in bits 0-31. A parity index iscoded in bits 35-50. An opcode is coded in bits 56-58. A block size iscoded in bits 59-61. A PCI device address is coded in bits 62-63. Bits32-34 and 51-55 are unused.

The block size is used to select the extent of a block addressed by theparity index. This is the number of consecutive 16 kilobyte blocks thatmake up the parity block addressed by the parity index. In oneembodiment, the block size is three bits, interpreted as follows: blocksize = 0 parity block = 16k block size = 1 parity block = 32k block size= 2 parity block = 64k block size = 3 parity block = 128k block size = 4parity block = 256k block size = 5 parity block = 512k block size = 6parity block = 1024k block size = 7 parity block = 2048k

In one embodiment, the bus interface 4301 is a PCI interface and the businterface 4302 is a PCI interface. Each of these PCI interfaces includesa read control to control reads from the caches 4218 and 4220. The readcontrol reads data from the respective output buffers 4330, 4331, 4348,and 4349 as needed. On completion of a PCI transaction, the outputbuffer is cleared. Each PCI interface also includes a write control tocontrol writes to the input buffers. The write control adds an addressword to the start of a data stream and control bits to each word writtento the input buffer. In the case where parity is generated and data issaved, the write control: determines which cache 4218, 4220 gets thedata; assigns parity to the other cache (that is, the cache that doesnot receive the data); and adds control bits to the data stream. Addresswords are typically identical for the various input buffers, but addedcontrol bits will be different for each input buffer. For paritygeneration, or regeneration of lost data, the data in transit is storedin one of the feedback buffers 4338, 4339, 4341, or 4340. The feedbackbuffer is cleared on completion of a data stream operation.

As described above, each data block written to an input buffer hasaddress and control bits inserted into the data stream. The control bitsare as follows:

-   -   bit 0: identifies a word as an address/control word or a data        word    -   bit 1: set to tag last word in a data stream    -   bit 2: enable/disable XOR (enable/disable parity operations)    -   bit 3: for an address word, specifies type of addressing as        either:        -   index addressing (for parity and regeneration data)        -   direct addressing (for normal data)

For operations that include an XOR operation, the XOR destination is a“parity block” in cache (e.g., in the cache 4218 or the cache 4220).When a parity block is addressed the address is calculated from acombination of: the parity index field from the PCI address word; thelower bits of the PCI address bus (the number depending on the blocksize); and the block size field from the PCI address word. Once the ASIC4310 calculates the parity block address for the first PCI data word,this address is incremented for each subsequent data word.

The parity block address can be generated from the PCI address wordusing one of two methods. The first method is to concatenate the parityindex with the lower bits of the PCI address word. The second method isto sum the parity index with the lower bits of the PCI address word. Ineither method, data is typically aligned to a natural boundary (e.g.,16k blocks to a 16k boundary, 32k blocks to a 32k boundary, etc.).

The CPU 4205 queues network transaction requests to the networkinterfaces 4214 and storage transaction requests to the storageinterfaces 4212. In one embodiment, the network bus 4201 is amemory-mapped bus having an address word and one or more data words(such as, for example, a PCI bus) and queuing a storage transactionrequest involves sending an address word and one or more data words to aselected network interface 4214. In one embodiment, the address wordincludes opcode bits and address bits as shown in FIG. 44. The datawords provide information to the selected network interface 4214regarding what to do with the data at the specified address (e.g., whereto send the data and to notify the CPU 4205 when the data has beensent). In one embodiment, the selected network interface 4214 views thedata engine 4210 (e.g., the ASIC 4310) as simply a memory to use forretrieving and storing data using addresses in the address word includedin the network transaction request. In such an embodiment, the networkinterface 4214 does not know that the data engine 4210 is interpretingvarious bits of the address word as opcode bits and that the dataengine. 4210 is performing operations (e.g., parity operations) on thedata.

The storage interfaces 4212 operate with the data engine 4210 (e.g., theASIC 4310) in a similar manner. The storage interfaces 4212 view thedata engine 4210 as a memory (e.g., a simple cache). The storageinterfaces 4212 communicate with the disks 140, 141 to retrieve datafrom the disks and write data to the disks. The data engine 4210 takescare of assembling parity groups, computing parity, recovering lostdata, etc.

“Hiding” the parity calculations in the data engine 4210 offloads theparity workload from the CPU 4205, thereby giving the CPU 4205 more timefor metadata operations. Moreover, using a portion of the memory-mappedbus address word allows the CPU 4205 to send commands to the data engine4210, again offloading data operations from the CPU 4205. The commandsare associated with the data (by virtue of being associated with theaddress of the data). The network interfaces 4214 and the storageinterfaces 4212 (which, themselves are typically network-type interfacessuch as Fibre Channel interfaces, SCSI interfaces, InfiniBandinterfaces, etc.) are unaware of the opcode information buried in theaddress words. This allows standard “off-the-shelf” interfaces to beused.

In one embodiment, the CPU 4205 keeps track of the data stored in thedata caches 4218 and 4220, thus allowing the server 130 to service manyclient requests for file data directly from the caches 4218 and 4220 tothe network interfaces 4214, without the overhead of disk operations.

Although the foregoing description of the invention has shown, describedand pointed out novel features of the invention, it will be understoodthat various omissions, substitutions, and changes in the form of thedetail of the apparatus as illustrated, as well as the uses thereof, maybe made by those skilled in the art without departing from the spirit ofthe present invention. Consequently the scope of the invention shouldnot be limited to the foregoing discussion but should be defined by theappended claims.

1. A method for storing data in a computer network, comprising:determining a size of a parity group in response to a write request,said size describing a number of data blocks in said parity group;arranging at least a portion of data from said write request accordingto said data blocks; computing a parity block for said parity group;storing each of said data blocks on a separate disk drive such that notwo data blocks from said parity group reside on the same disk drive;storing said parity block on a separate disk drive that does not containany of said data blocks; and redistributing said parity group to improvestorage efficiency.
 2. The method of claim 1, further comprising storingmetadata to describe a disk and logical block location of each of saiddata blocks and said parity block.
 3. The method of claim 1, whereinsaid redistributing comprises combining a first parity group having afirst size and a second parity group having a second size to produce acombined parity group having a third size, wherein said third sizespecifies a number of blocks that is, at most, one less than the numberof disk drives available to store data from said parity group.
 4. Themethod of claim 1, wherein said redistributing comprises splitting afirst parity group into a second parity group and a third parity group.5. The method of claim 1, further comprising allocating a new paritygroup from a pool of available parity groups.
 6. The method of claim 5,further comprising generating parity groups for said pool of availableparity groups from unused disk space.
 7. The method of claim 5, furthercomprising generating a plurality of differently-sized parity groups forsaid pool of available parity groups from unused disk space.
 8. Themethod of claim 7, further comprising splitting a parity group in saidpool of parity groups to produce two smaller parity groups in said poolof available parity groups.
 9. The method of claim 7, further comprisingcombining one or more parity groups in said pool of parity groups toproduce a combined parity group in said pool of available parity groups,said combined group larger than said one or more parity groups.
 10. Amethod for storing data in a computer network, comprising: storing afirst parity group comprising first data blocks and a first parityblock, wherein said act of storing the first parity group comprisesstoring each of said first data blocks on a separate disk drive suchthat no two of the first data blocks reside on the same disk drive;storing a second parity group comprising second data blocks and a secondparity block, wherein said act of storing the second parity groupcomprises storing each of said second data blocks on a separate diskdrive such that no two of the second data blocks reside on the same diskdrive; and redistributing said first parity group and said second paritygroup to improve storage efficiency.
 11. The method of claim 10, furthercomprising storing metadata to describe a disk and logical blocklocation of each of said first data blocks and said first parity block.12. The method of claim 10, wherein said act of redistributing comprisescombining the first parity group having a first size and the secondparity group having a second size to produce a combined parity grouphaving a third size, wherein said third size specifies a number ofblocks that is, at most, one less than the number of disk drivesavailable to store data from said combined parity group.
 13. The methodof claim 12, wherein the first size of the first parity group is largerthan the second size of the second parity group.
 14. The method of claim10, wherein said act of redistributing comprises splitting a firstparity group into a third parity group and a fourth parity group. 15.The method of claim 10, further comprising allocating a new parity groupfrom a pool of available parity groups.
 16. The method of claim 10,further comprising storing metadata that specifies at least oneGnid-string.
 17. The method of claim 16, wherein said Gnid-stringcomprises a collection of gnids.
 18. The method of claim 17, whereineach of said gnids comprises information for locating a specified gnode.19. A system for storing data in a computer network, comprising: meansfor determining a size of a parity group in response to a write request,said size describing a number of data blocks in said parity group; meansfor arranging at least a portion of data from said write requestaccording to said data blocks; means for computing a parity block forsaid parity group; means for storing each of said data blocks on aseparate disk drive such that no two data blocks from said parity groupreside on the same disk drive; means for storing said parity block on aseparate disk drive that does not contain any of said data blocks; andmeans for redistributing said parity group to improve storageefficiency.
 20. The system of claim 19, wherein said redistributingcomprises combining a first parity group having a first size and asecond parity group having a second size to produce a combined paritygroup having a third size, wherein said third size specifies a number ofblocks that is, at most, one less than the number of disk drivesavailable to store data from said parity group.